Vision Keynote Splash 2026

Where AI is at the center of financial operation, not a bolt-on tool. And where agents are part of your finance team, working, reasoning, acting, all within the governance, security, and audit rules finance requires.

This is not experimental AI. This is finance AI at scale. Generative, quantitative, and agentic AI coming together. So finance can reconcile instantly, optimize continuously, detect risks and opportunities before they happen, and predict what's next.

In the age of AI, it's more important than ever to have the financial system strategy and topography that has been rationalized so that you can get the most value out of these new technologies. And behind it all, OneStream, your finance AI platform.

Where AI isn't added on, it's natively built in and purpose-built for finance. Sensible AI agents to extend your finance team with AI that acts. Sensible AI studio to automate the financial workflows that slow you down.

Sensible AI forecasts to plan faster and with greater accuracy than ever before. All unified on the OneStream platform. Using the corporate data and financial context your team trusts. Surface within the workflows your team uses to run the business.

And extend it with an agentic layer so your team can use any agent they choose. Within the trusted financial intelligence and governance only OneStream can deliver. Faster closes, more accurate forecasts, real-time insight, decisions without delay.

With Sensible AI forecast, our forecasting accuracy have improved dramatically. We have shortened our forecasting time frame down from two days to 10 minutes. No more waiting. No more uncertainty. No more looking back.

Only forward. Finance has changed. This is forward finance. This is OneStream. Please welcome OneStream founder and chief executive officer Tom Shea. All right. Hello. How's everyone doing? Good? I've been thinking a lot about 2026 and how I've been feeling this year.

And I would characterize it as nervous excitement. And why do I say that? Basically, I'm feeling that we're in high stakes mode. Not because of inflation. Not because of But because of the pressure that we all are feeling to do more faster than ever before.

The truth is, the world is now changing and accelerating faster than we've ever experienced. Markets shift overnight. Demand moves in real time. And now, things that used to take months, decisions that we had to contemplate, now are expected to be done in minutes.

Finance is no longer the scorekeeper. It's the control tower for your business. The future isn't reporting on what happened. It's deciding what happens next. The market is now demanding that you get real value out of AI at scale.

I know we're all tired of hearing AI over and over and over, but that's the fact that we all face running businesses. While most finance orgs have been experimenting and finding pockets of value with artificial intelligence, there's a growing belief now that you must fundamentally rethink a lot of processes in your business in order to extract that value that AI can bring.

I know we're all feeling that. Well, we call this forward finance. A new operating model for the office of the CFO. Where AI doesn't get replaced, it doesn't replace finance, it amplifies it. After benchmarking dozens of companies, we found that the most forward-looking are using AI to augment their staff, augment their workforce, help you be more productive, optimize operations, look for ways that you can improve your business, and transform core financial processes like planning, forecasting, and other analytic tasks.

Our research uncovered, though, that the AI gap isn't coming to finance. It's already widening. And there are three things that are holding finance back. These are consistent. These are themes that you're used to, but they're even more important in the agentic world.

That's poor data. It's lack of controls and context around that data and weak governance. Finance leaders agree that trusted data is critical. Yet, half of our study, the folks in that, admitted that they've made decisions on bad data in the last year.

And even more importantly, and the kicker, of those organizations that made bad decisions, they were 4x more likely, 4x more likely, to be big users of AI. So think about that. That's risk. Why is that? Public AI models, they lack context of your business, your data, your rules, your operations.

And without context, AI is just going to deliver fast confusion. Finally, there's governance. AI can generate answers. But in finance, if you can't trace it, if you can't audit it or defend it, it's not insight.

It's just risk at scale. So, as a recovering finance professional, I've seen this before. I've been in your shoes. I've experienced this. And I want to share a little bit of that story with you. As an eager, young financial analyst and accountant, I wanted to be a CFO earlier in my days.

I was at the dawn of another force multiplier, another huge productivity gain. These office productivity suites, things that we take for granted today. Right? We saw our productivity skyrocket and the possibilities seemed endless because of Excel.

Instead of being contained to a 10 key and a printout from a mainframe, we were unleashed because of Excel and the models that we could do. Yet, while those benefits were real, we also experienced another problem.

We now replaced one version of truth with a thousand almost rights. All right? So, that's something that we've all been dealing with. And we entered into what we would all call the reconciliation loop.

Right? The endless exporting of data from one system, looking at it in a spreadsheet, tying it out to another spreadsheet, only to verify it in a meeting and argue with somebody else because they came with a different number.

It's all the things that we've talked about for years. But, we've gotten a lot of productivity out of these tools. So, fast forward to today. Why is this relevant? We're seeing this even more. AI introduces a similar paradox.

You can think of the tools and the productivity that we're seeing coming to you, except that it's at an exponentially larger scale and pace. So, public LLMs and agents like Copilot, Claude, they unlock new scale, potential for analysis, and business efficiency like never before.

But, finance teams can literally do millions of things with AI. They can automate routine tasks. Right? You can build formulas, reports. You can get so much leverage on this new technology. And I know you're all hearing it.

You're probably experiencing it now. We're really seeing the dawn of this capability. But, again, generic AI tools struggle to verify data and provide auditable reasoning that finance requires. They lack the business context and controls.

Finance can't get verifiable data that's trusted and the information that it requires to make decisions on answers that come back from just plain generic LLMs. So, finance doesn't need more AI tools. It needs an AI operating system.

Generic AI gives you answers. Finance AI gives you answers you can defend. That's why we made sensible AI. A portfolio of AI solutions purpose-built for the office of the CFO that lives natively in the OneStream platform.

Starting with our flagship product, sensible AI forecast, to deliver faster, more accurate forecasting capabilities. Followed on by sensible AI studio. A series of purpose-built AI algorithms that can help you automate all the different processes that you're being asked to find efficiency for.

And then, finally, sensible AI agents. Something that we're all so excited about and everybody's experiencing. You know, what is this going to mean to me? And what is this going to mean to my career? Well, it can help augment your staff.

It can help take away the mundane work so that you can focus on the more value -added work that the business wants from you. In OneStream's vision, forward finance is really not going to be in a situation where AI is replaced.

In the world of analysts and the world of accountants, finance isn't getting replaced. AI is in an amplification mode. We're entering into a new era of work where finance will work in three ways. First, you're going to continue to use OneStream in the way that you've always experienced it.

Teams will continue to access, analyze, and work directly within OneStream's user interface. Second, teams will increasingly be augmented by the specialist capabilities of analysts, giving you more and more opportunity to become efficient.

Search for key data, generate reports, make recommendations, and automatically run plans, trends reports, and analysis. And finally, over time, as confidence grows with artificial intelligence, you're going to see specific tasks and scenarios where the agents have the opportunity to autonomously interact with the system by safely operating within the governance, audibility, security of the OneStream platform.

So how is OneStream going to drive this future? You've heard me say AI at least 100 times in this presentation so far. So let's think about this for just a second. What's really impactful? We're very excited to introduce our agentic layer.

This is a modern integration layer to all major AI platforms. We connect you to whatever agent you choose. So what does this mean for you? This is the choice to work where you want, within the agentic system that you want, but maintaining the governance and reliability of the OneStream platform.

Whether you use OneStream specialty agents, Claude co-work, co-pilot, co-pilot co-work, you control the interface, and OneStream will control the truth. So any agent you choose with the governance you need.

So now let's talk about how the three core pillars of our platform contribute to this vision of forward finance. Our first pillar, core finance, is so important. It's foundational. Because agents are not useful if they don't have reliable data.

And our core is the foundation of OneStream's reliable data that helps you achieve the things that you must do. And it's now going to be even faster and more efficient. We continue to make investments in this area of the platform.

Second, our operational planning. This is a very critical area, right? Because this is where you add the most value to your business. What do I mean by that? For myself, for our finance team, I want them to help us steer the company, not just report on it.

So understand what's happening daily, weekly. That's what our operational planning, our operational forecasting, and basically our agile financial analytics is all about. This enables you to take your fast-changing operational data and financialize it so that you can use it for meaningful decision-making.

Third, our finance AI. This is what amplifies everything. These are the things that you need to do. And it's AI that's built in, not bolted on. It's purpose-built for finance. And now, it integrates and interacts with your broader agentic frameworks.

Every one of you at a company, every one of your IT teams, every one of your executive teams, you're going to be asked to use broader agentic capabilities. And you're going to need finance tools that can operate reliably inside of that.

That's really what we're talking about here, and it's so important. The OneStream platform, though, is now wrapped in our broader plug-and-play architecture. This is our commitment to make OneStream easier, faster, smarter.

Why? As we keep adding more and more value to the platform, we want to make sure that you can get that value more quickly, more reliably, and at a lower cost. That's what our plug-and-play architecture is all about.

The rest of the Splash keynote is designed to do just that. The OneStream product leaders are going to take you through the three pillars and really showcase the investments that we've been making. And it's across the entire platform where we're focused on driving more and more value for you and giving you and delivering innovations across every one of those areas.

You're going to hear from customers and partners embracing the platform and how they're using that to create a competitive advantage because of the consistent data that it unlocks. I'll be back later to sum it all up and to hear and to kind of bring to close all the value that you're going to hear.

This is such a great presentation. I say this every time we're at Splash. And for the first time, I'm not going to be talking to you for an hour and a half straight. We're going to bring our team out and let them talk to you about all the great innovations that they've been working on.

So when we think about this, our product leaders are going to share how OneStream empowers you to be a forward finance leader. So buckle up. This is going to be a great show. I can't wait for you to experience all the wonderful things we've been working on.

I'll talk to you soon. Please welcome Executive Vice President of Product and Engineering, Jeremy Gutman. As you just heard from Tom, business is demanding more and more of finance every day. And with the prevalence of AI expanding, your core, your financial core is more important than ever before.

So what do we mean? We mean the need to close, to consolidate, to plan and report. Forward finance needs a strong foundation. And these are the things that you must do. Now, with AI, it introduces non-negotiables.

And Tom touched upon them. Your data needs to be solid, secure, efficient, accurate, auditable. These are the key ingredients. And this is why we're so focused on the core. And that's why we've been investing so heavily.

I'm really excited to highlight three investments that we've made over the past year. So you can understand how this is coming together. And it's been a busy year. It's been an amazing year. About 11 months ago, we focused on the first leg of our journey, which is how does data come into the platform and how do we accelerate it? And so with the release of version 9, I'm very excited that ingestion of data is now 20 times faster than it's been before.

Think about what 20 times means, right? It's more time to do other things that are higher value, right? And as well, it increases our capacity to handle and address more data, which is what you want as you tackle more and more use cases.

So that was step one, milestone one. The next one, very excited. It's new. It's part of the release that just launched last month. And what do you do after you've got the data in the platform? Well, you want to consolidate it.

So we just made consolidation four times faster. Four times. You don't need to change your implementations. You don't have to adjust business logic. You upgrade to this latest version, and you benefit from both of these major achievements.

And as you can see, we're working our way through the core so you can continue to address more. Now, the last leg of the journey here is you need to visualize it and work with it. And so we're excited that this latest release is now 20 times faster in the browser experience.

Let's face it. Grids are the backbone of everything that you do, and now it's 20 times more responsive. Thank you. You can see our focus on where and how we can deliver for you and where we can meet you where you work.

And as we drill into that, let's face it, finance works and loves spreadsheets. And maybe more specifically, we love Excel. Me too. It's okay. Now, we've had an Excel experience, but really what we wanted to do was evolve forward and help take out the friction with some of the newest tools that are available with Microsoft 365.

And that's why we're excited to announce the availability of our Excel add-in for Office 365. Now, you have the Excel experience in the client or in the browser. Take away the friction, certainly the challenges, as you all know, when it comes to upgrades.

And it's not the same experience you've had today. We've expanded it. We give you new features like in-cell type-in. And you're going to see more about this as we demo it. It really unleashes and opens up new opportunities.

Now, we're not going to stop here. We're going to continue to expand into other areas of the Office suite as we tackle more and more and across the ecosystem. And you'll hear later this afternoon when we talk a bit more about Copilot and Teams.

It's very exciting. Now, I know you guys are excited about Excel. I've been here for a day and a half. I've already heard it as the kind of message started to get out. And the feedback was fantastic. So we know that you're getting real benefit.

But I'll say it's also nice to know when the market acknowledges it. And we're now a four-time leader in the closing consolidation Magic Quadrant. Our goal, right, to unify all of your data, to give you that one lens to complete the tasks you must do.

What's really great about what we find with the Magic Quadrant is we're sited specifically for our vision. And that's a shared vision, shared with all of you as we partner together to build and expand.

And you see us executing on that vision as we look to move to power the complete modern financial close. It's an end-to-end process automating your repetitive tasks and going from that first transaction creation all the way through to your financial reporting.

Now, this has been our focus. We've been partnering with you, and we've done, frankly, amazing things together. When we look at the modern financial close capabilities, we've been evolving for years. But just last year, we introduced anomaly detection into account reconciliations.

We expanded transaction matching to heights, 200 million transactions per period. And that's from you. You asked for more in transaction matching, and we were happy to partner and deliver it. And late last year, the newest entrance, journal entry manager.

The feedback here has been fantastic. Customers are telling us about the manual tasks it's eliminating and the optimizations that you see. And we're going to continue to give you more features and more functionality.

Now, we're not going to stop there when it comes to close, because we want to ensure that not only do we have the functionality, but we've got the right experience. And we're proud to introduce the modern financial close experience.

What is it? It's a simplified user experience with guided workflows that brings it all together in one lens. So rather than me talk about it, why don't we take a look? The modern financial close allows organizations to shift from a concentrated end-of-period scramble towards a more continuous daily process.

This Genesis-based unified control center provides real-time visibility into modern financial close processes in a single centralized platform. A modern task list transforms from a static to -do checklist into a dynamic execution engine.

It is no longer just a record of what was done, but an active driver of the entire financial close process. OneStream's high-volume transaction matching solution transforms a manual labor-intensive process into a strategic engine that accelerates your financial close and eliminates month-end bottlenecks.

By automating up to 95% of routine matches, your team can shift their focus from manual data entry to high-value exception management and analysis. This real-time visibility ensures you maintain a continuous cycle posture, providing leadership with accurate, data-driven insights whenever they are needed.

Our latest Journal Entry Manager solution centralizes your data, replacing manual spreadsheets, dynamic workflows, ensure a single source of truth for every entity. By pre-validating data, organizations ensure that only clean, accurate data ever reaches their ERPs, transforming the journal process into a strategic, audit-ready operation.

Journal Entry Manager is designed to empower our customers with easy deployment and maintenance, giving finance teams full autonomy to configure workflows and templates without relying on heavy IT support or outside consultants.

AI-powered account reconciliations unify your financial reporting and close processes by loading your trial balance. Once, both finance and accounting work from the same data, ensuring alignment and streamlining the close.

With built-in anomaly detection powered by Sensible AI Studio, OneStream can automatically surface exceptions using pre-configured rules, like spotting documentation gaps or unusual balance changes. This lets teams focus on managing risk and resolving the issues faster and improving transparency, control, and productivity.

OneStream provides the ability to drill down from balance sheet totals to underlying reconciliations, providing a single line of sight across the entire data value chain. This capability transforms a static financial report into a transparent, audible process that ensures every dollar on the balance sheet reflects actual business activity.

Embedded AI routines from Sensible AI Studio power an intelligent and automated narrative analysis. A narrative analysis transforms a standard financial table into a strategic tool by explaining the why behind the numbers.

While a numeric report may show a large loss in accounts receivable, A narrative report provides the essential context, such as improved collection efforts to help leaders make informed decisions rather than reactive cuts.

And that's just a sneak peek at what's coming for this evolution of the modern clothes experience. Built on top of our Genesis plug-and-play architecture, that's what makes it so easy and fast to implement.

Because we know that you must close your books. So what? So you can then focus and plan for the future. So you can plan for any level of your business. Maybe it's corporate, divisional, location, product, and being able to do it on one unified platform, clothes and planning.

And that's why it's no surprise that in this room, two-thirds of you are using OneStream for both financial clothes and financial planning. And, you might expect, not a surprise for us to be a five-time leader in the planning quadrant.

Thank you. And what does this show? Well, certainly key features that have been in the platform that you know and well, like extensible dimensionality, are central to be able to plan and analyze at the right level.

And, again, when I look at kind of the real takeaway here in the magic quadrant, I'm completely touched by this idea that we're noted for our ability to execute. And why? Because the ability to execute is about outcomes.

The founding of this company was around the success of you, our customers. And so ability to execute is something that we deeply feel. And as we've continued to focus and evolve here, outcomes are driven faster by accelerating the time to value.

And we've been focused on this. And I'm excited to announce the release of OneStream Financial Planning Express. We've taken the lessons learned with all of you based on thousands of implementations. We've packaged it.

And we're making this available for you to release or deploy in weeks. It's templates. It's reports. Giving you value faster. Now, if you're using other Express products in our family, great. But you don't have to to use Financial Planning Express.

It's available and has value to all customers. And you're going to see us continue to push in this direction where we can package functionality that anybody can benefit from so that you can focus on implementing and addressing the next use case that will truly transform your business so that you can amplify the core and tackle what you must do.

Now, OneStream co-founder, Craig Colby, famously said, you amplify the core so that... Nice. All right. So you can do more. Right? What did Craig mean? He meant that when you have a unified view of your corporate data, when you've automated the close and reporting process, it gives you time to step back and breathe and look for opportunities to be more strategic and help guide operational teams.

Real value. Unlocking real value. And that's why we created the Planning and Analytics Pillar. It is designed very specifically for you and in response to your needs. Right? Because we know finance sits in a unique position.

Right? Understanding business objectives, understanding data to help drive the operational teams. And that's why you're being asked to do more. And it's a tremendous opportunity, and it's a trend that we see happening.

And this prediction here, it's happening right now. You can look out at a number of cases as recent as today where you see the CFO role and the COO role combining, coming together. We saw this coming.

We saw this opportunity, this finance-led operations era, and that's why this pillar is so important to us. Now, you know it too, and you've been implementing and delivering solutions. Right? And so we're all leading in this space as we continue to go forward and help our 1,800-plus customers.

So I could talk more about it, but you know the best storyteller is always you, our customers. So I'd like to introduce Milo's Tea. Milo's Tea is a multibillion-dollar women-owned beverage powerhouse.

And when it came to OneStream, they had real struggles. Struggles with spreadsheets, manual workarounds. They had tried other tools, but the tools couldn't scale, couldn't meet their needs. And it's one thing to have the challenge meeting your needs today, but what they found is it was actually hindering growth for tomorrow.

So what I'd like to do now is welcome to the stage Milo's CFO to hear more about their story. Please welcome Milo's Tea, Chief Financial Officer, Emily Backstrom. Hello, Splash 2026. I am thrilled to be here to share Milo's journey with OneStream with you today.

For those of you in the room not familiar with Milo's, we are a family-owned, certified women-owned company known for crafting the number one selling refrigerated tea and the fastest growing lemonade in the United States.

And we are on track to be a billion-dollar brand in retail sales by the end of this year. Thank you. Milo's is the category leader in refrigerated beverages. We use high-quality, real ingredients, no dyes, no acids, no preservatives.

We're available in most major retailers across the United States, over 60,000 locations. We operate three large-scale, state-of-the-art manufacturing facilities, employ approximately 1,000 associates in the communities of Birmingham, Alabama, which is our hometown, Tulsa, Oklahoma, and Spartanburg, South Carolina.

We're currently in our third generation of leadership. Our current CEO, Tricia Walwork, is the granddaughter of our founders, Milo and B. Carlton. Now, what you may not know is Milo's has not always been a tea company.

We actually were founded on the north side of Birmingham in 1946 as a hamburger stand right after World War II when Mr. Milo returned to the United States. The restaurant was so popular, the family began to franchise the restaurants over time in the 1980s.

But what they started to learn is that people were actually coming to the restaurant just to buy the tea. So they made their next big decision. They sold the franchise and capitalized our first manufacturing facility and started bottling sweet tea and selling it just down the road in the Piggly Wiggly in Birmingham, Alabama.

Now, fast forward to today, we're in all 50 states. We offer 11 flavors of tea and lemonade and we aren't done yet. As a family-owned business, we think generationally about impact. We want to ensure we're not just delivering delicious beverages today, but we're doing our part to protect communities for the environment over time.

We are proud that our manufacturing facilities are certified platinum zero waste operations. We donate 1% of our annual profits to organizations focused on education, sustainability, community disaster relief, and we're very proud we were named number three most loved workplace in America by Newsweek.

Thank you. Over the last 10 years under Trish's leadership, we have exponentially grown consumer demand and all functions of the company have been on a journey to step change our capabilities. We chose to partner with OneStream because with growth, expanding distribution, and increasing product and channel complexity, we knew we needed to have a more agile financial planning essential for a future success.

Now, before we partnered with OneStream, we did have manual, spreadsheet-heavy processes, systems that couldn't scale with our growth, and fragmented data and visibility. Maybe some of you are in the same situation.

Our legacy systems give us limited visibility to drill down. We couldn't connect assumptions with results. And our close cash flow, CapEx, and cost accounting processes were just frankly very manual and time-consuming.

We lacked workflow, governance, and agility. In short, our FP&A team could not move at the pace of the business. And we were in a position to provide critical insights. So we knew we needed a different solution that could grow with Milo's.

And Milo's grows pretty fast. You know, inside of Milo's, we talk about we all need to 10 times ourselves in order to keep pace with the explosive growth of the business. Well, we needed a CPM tool that could also 10 times at that pace and grow with us as well.

The good news is what we found in OneStream is what we believe is a platform built for the long term. And why is that? First and foremost, OneStream is a single, unified platform, and it's built to scale over time.

We can grow with OneStream. It's a tool that our finance and accounting team can maintain without extensive support from IT resources. And we could see line of sight to having a very integrated forecast across the P&L, cash flow, all the way through the balance sheet and over a multi-year horizon.

We also saw the agility to do scenario planning, agility that just frankly was too cumbersome in our old manual system. And finally, we saw OneStream investing in our future capabilities. We just heard Jeremy talk about some of those just a moment ago.

And perhaps you're like the Milo's team who's here this week looking to learn more about sensible AI at this conference as well. So we did find OneStream to be a truly transformative platform for us. It's not just a budgeting tool.

Life with OneStream looks different. It looks streamlined, efficient, more visibility and insight, and supports our continued growth and complexity. We were able to see a lot of benefits very quickly.

It's intuitive. It's user-friendly. It's become our single source of truth. And as we think about it, we were able to see really remarkable results. You can see many numbers here up on the screen. But I will tell you, to me, what has been the most important win, it's the smiles on my finance team's face.

I have a finance team who's energized, who can unlock insights at the pace of the business. They're spending weeks, their time now with their business partners, not tied up in manual forecasting processes.

But let's be honest, we have lessons learned, too. We all do, right? The first is implementation partner selection is critical. And I have to give a shout-out to the AIT team, who I know is here, who has been just an incredible partner for Milos through our transition to OneStream.

The second learning is bottlenecks moved downstream in the system. We were talking more about data and governance, transparency through the process. So we had lessons learned for sure. My ask is come to the Milos team who's here this week, ask them more about our lessons learned and our growth journey with Milos in OneStream.

And in return, we would love to share with you one of our delicious teas and lemonades, which are on the front porch just down the hallway. And we want to hear your lessons learned, too. We're going to be stronger by hearing all of our lessons learned together.

So thank you in advance for that. And as Milos continues our growth journey, new flavors, new channels, new formats, new platforms all around the horizon. And as our team knows, we're on a journey not just to a billion-dollar brand, but a billion-dollar brand and well beyond.

We will also continue our growth stream with OneStream. So what's next for us? As simple as it sounds, job number one is continued learning. OneStream is not a one-and-done. We are on a journey to unlock the system's capabilities over time.

The second is we have more to do in the space of cash flow and capital enhancements. Anyone who feels like they're ahead of the curve on that, please come find my team. And then, as I mentioned, we are here at Splash to learn a lot about sensible AI as well.

We look forward to learning more, too. So we are very grateful to OneStream, AIT. I have to say a thank you to my team for all the work that they have done. It has been a true partnership that is helping us fuel our growth.

So as we like to say at Milo's, let's grow. Thank you. Thank you, Emily, for sharing that story. You know, what strikes me is how you can see that Emily and her team, finance, is really now driving the operational rhythm of their business.

Right? And with the right tools, with the right solutions, we can really have finance without limits. And that's why we're so focused on this operational pillar and we're so focused on continuing to expand what we can deliver so you can expand into this strategic remit.

How do we think about enabling you further, more modeling, more planning scenarios, so that you can have the solutions you need to lead your organization? Now, in this finance-led era, we see that the requirements are a little different and continue to change as the market changes.

And we see the need for maybe thinking about planning and the modeling we do a new way. What's causing us to step back? Well, think about what we've talked about so far. We talked about volatility, the pace of acceleration, the need for agility.

So, speed, agility, and forecast accuracy. Right? That's the recipe for transformation. Right? And you heard a little bit of this just now with Milo's. They needed to be able to address more data with increased granularity.

Right? So, they could plan more effectively for tomorrow. They needed to be able to see into their business more. They needed to be able to find the signals in that highly granular data so that they could respond to them.

So, how do we think about signal and response as kind of a key orienting concept for new tools? Well, we can look at another transformation for inspiration. Navigation. Right? We started navigation with maps.

Right? Single version of the truth. Maybe you had the triptych, if anyone knows what that is. But we started with maps. Right? And where'd we go next? Well, we took those maps and now we've got semi-intelligent routing systems to get us from point A to point B.

Right? What do we have now? Well, we have the missing piece. All right? Today we have amazing apps like Waze that provide us the single version of the truth. Right? The maps. The ability to route from A to B.

But now, now I can see the signals that are happening. Okay, so what happens when you're on your journey? Well, you've got traffic, construction, maybe just slow-moving vehicles. Right? But all of those details, all of that insight is available to you on one platform, one experience, and given real-world changes, like what happens in the market, you can stay on the fastest, safest, most optimal path.

Right? So, this route optimization is a good way to think about the type of change that we see happening. Right? When I'm driving, I need the signal presented to me. I don't want to think about recalculating the map or changing things.

Right? I want that signal to be given to me as the human in the loop, and then based on that, I want to choose the right response. I need to be able to cognitively digest what's happening and think, this is what we do every day.

This is what needs to happen with our planning tools. Enable us to enter this cognitive planning era. This idea that market changes happen, and you need to be able to learn from that. You need to be able to adapt to those changes automatically.

I don't want to have to go reconfigure a model. I'm not going to reconfigure the map. Right? I want my models to understand the dynamic nature of what's happening and surface that to me. That's what we're talking about when we say cognitive planning.

It's this idea that we don't know the absolute answer. We know the value and the outcome we're trying to achieve. We're not going to goal seek our way there. We're going to build models that are flexible and enable us to adapt and change.

This is why we created the dynamic analytic services, things like dynamic dimensions, dynamic cubes. We were laying the foundation, the foundational pieces to enable us to build and deliver this reality.

And so today, we're going to talk about a new tool that continues on this vision. I'm very excited to announce line item modeling engine. It's one engine that solves a whole host of operational needs.

Most importantly, it's no code. You can configure your calculations, your data needs, and it's extensible. Line item modeler delivers the ability to learn, adapt, and model faster. And again, all built on our AI native platform.

We talked about the dynamic analytics services, natively works. Our AI chat capabilities, natively works. That's what it means to be designed on one platform because everything comes along with it. And again, the data you can trust and that you can feel confident in.

So how do we bring this to you and make it even easier to implement? Well, we're going to announce our first two packages that are built on top of line item modeling. Fixed term planning and duration-based planning.

Now, fixed term helps you tackle things like projects, leases, subscriptions, while duration-based is good for contracts and grants. So let's put that in some context. You know, if you're looking at large capital projects, fixed term would be a great one.

If you're looking at grants, maybe in the higher ed space, another opportunity. So as we continue to look at the things that move your business the most, what's one of the biggest line items on the P&L? Well, it's people.

Their greatest asset, and there's some cost there. So we're excited to announce our workforce planning solution built on top of line item modeling. Workforce unifies finance, HR, and operations. You can model headcount, compensation, labor, and you can see that impact as we talked about with the dynamic capabilities.

You can see it across your business, right, and really use it to drive outcomes on top of the trusted data. This is about how we can deliver value faster and faster, and we're doing that with Workforce Planning Express.

Now, what I'm really excited about here is not just the package based on hundreds of implementations that we've done, right, not just that you have deployment methods and templates and reports to accelerate, but I'm most excited about just what that acceleration means.

So there's one story in particular. We worked with the GSI and they used Workforce Planning Express, met with their customer, took in the requirements, and the next day showed this demonstrably in the solution.

That's one day to implement Workforce Planning Express. That's value, real value, and real quickly. So, this is how we jump in to the era of cognitive planning, and this is how we're meeting that need and meeting that call.

So, with so many great announcements, what do we got to do? We got to start planning today. So, I'm going to leave you now, but in the capable hands of Doug Kinchley, who's going to make this come to life.

All right. Before we get going, I'm going to need you to reach under your seat and you'll feel the seatbelt there and I need you to buckle up because we're going to go on a wild FP&A adventure here. So, on this adventure, I'm the manager of FP&A for a global retail business that has 100 golf stores that sell golf equipment.

And I'm responsible for making sure that those locations hit their forecast and meet their goals. So, right out of the gate, I see a big problem. In the blue bars here, I have a solid demand, but I don't have the inventory or supply to meet that demand.

So, before my boss comes into the office, I need to get to the bottom of what this gap is and what's driving it, and I need to figure out a strategy of how to recalibrate my plan to stay on track to hit our goals.

So, Excel is where I want to do that analysis. And with the new Office 365 add-in, whether I'm in the browser, on a Mac, on my PC, on my desktop, I have the power of my governed one stream data with the flexibility and familiarity of Excel.

Excel. So, the first thing that we're going to drill into here is we're going to look at our operational detail, and we're going to look at it by product and location for the last four weeks. And the one thing I really want you to spot here is I no longer need to put dimension tokens in.

I just describe what I want to see, and one stream does the heavy lifting for me here. So, let me just scroll down. All right. Total products dot base and then May base. I'll do the same for locations.

Total locations. All right. So, now, really quickly here, again, I have the dimension, just I have descriptions here of what I want to see, and one stream is going to do the heavy lifting for me. Now, as this renders the quick view here, a couple things I want to call out.

In the past, if I wanted to get the operational detail that's driving the financial results, I'd have to log into a legacy system, extract this data, and then I would have to consolidate it into some format that aligns to the forecast or do kind of the phone call, email, shuffle.

Let me format this. So, that typically goes along with, you know, this process. But in one stream, I have live operational data, and I'll format it here just to show you the trend we're seeing. This is live operational data pulling from the stores, right? And so, I'm no longer loading data.

It's just coming in live, and it's in context of the problem that I'm trying to solve, right? And so, really quickly here, what I'm spotting is I have excess inventory of my higher-end products, but I have high demand and not enough inventory of my lower-end products.

So, the question becomes, how can I take advantage of this excess inventory without eroding my margin? And so, one way to do that is introduce a rental line. So, I'm on a unified platform, and the benefit of that is that I can just start planning right away.

So, I'll enter my rental line here, and then what I'll do is I will update my product mix, and drag that, and then what you'll see here is when I submit this, it's going to instantly recalibrate my plan and re-update my product mix here.

So, in a couple seconds, I've gone from insight to an actual decision, but I can't plan here in a vacuum, right? And so, as I accept more demand and there's more traffic in the stores, there's other operational impacts that apply here, and one of those is workforce.

So, as I come into workforce planning here, we can see that it's already spotted that there's going to be more traffic in the store, and it's suggesting that I add an additional two headcount. So, I'm going to go add those employees here, activate them, and then as I submit this, we'll instantly see both the financial and operational impact of those changes.

All right. So, now we've, again, gone from insight to a decision to then the operational impact of that decision, and now I need to explain the plan. And the added flexibility of Office 365 when it comes to reporting makes it easier than ever for me to explain this plan.

So, let's jump in here and we'll start creating variance analysis here. All right. So, I'm going to grab my accounts. Notice I'm just grabbing the descriptions and pasting them below, and now I'm going to type actual 2025, 2026, forecast, and then again, 2026, forecast, revised, and now all I have to do is just add the quick view, and one stream does the heavy lifting for me here.

So, I'm pretty pumped about this. I don't know about you, but I'm Now, my boss is not pumped because she wants to see this on a tablet and a flashy dashboard. So, if I come back into the browser here, I can jump into this new scenario and all the changes that I made in Excel are available throughout the OneStream platform.

And so, I want to look good when I go into a meeting with my boss, right, because she's so nice. And I, no one's better than making me look good than sensible AI agents. And so, I'm going to have it pressure test and hit me with some of the hard questions and give me the answers to the test here before I go into that meeting.

So, I'm going to ask it for the main risks here. Forecast. Probably hard to see, but, all right. So, as this is running, it's analyzing this scenario, associated driver information, any other context associated with this.

and when it completes here, what it's calling out is this new scenario expects a major change in buying patterns without actually allocating marketing specifically to drive that shift, right. And so, again, it's going to make me look good with my boss.

So, we've covered a lot of detail in this little demo, so I encourage you to come see us at the Excel booth or the planning booth or come to the what's new, what's coming for Excel or the planning sessions.

But there's a couple things I want you to remember. The first is the power of bringing your operational detail into the context of the problem or the plan, right, because I can then go from driver to decision really fast.

The second is the improved usability provided by Office 365 and the improved flexibility in reporting so that you can plan how you think. So, thanks for coming on this adventure with me. Please welcome Executive Vice President of AI and Operational Analytics, Andrew Shea.

Hi, everyone. I'm incredibly excited to be up here today to talk about all the latest and greatest sensible AI innovations. But before we do that, I want to anchor in on what I believe the key word of 2026 is, and that's pace.

You heard Tom talk about the need to make decisions that used to take months that now need to happen in minutes. You heard Jeremy talk about the incredible pace of innovation that we have infusing into the core platform the mission critical business workflows, the engine development speed capabilities as well, and the user experience faster grids.

When you think about all that, there's a third key element that I want to hit on as it relates to pace, which is what's going on actually on the outskirts of the Office of Finance. And to me, what that means is what we're seeing in the world of agents, particularly within the world of software, product, and engineering.

And I think one of the best stats to anchor on to begin is the fact that Anthropic, one of the leading model providers, released 73 product releases in 53 days at the beginning of 2026. That is incredible, incredible speed.

What does that mean for us as a developer or even as someone looking for productivity? Even within the Office of Finance. That means there's new model capabilities, new ways to make myself faster, my team faster, my organization faster.

At the same time, I have an anecdote that's personal to myself. To this day, still one of my favorite things to be able to do is get a full day where I get to put on a hoodie, put up my hood, put in earbuds and put on some good music and just code away all day.

Now the reality is I'm actually not coding anymore. My role has fundamentally changed as a software engineer. My role now is to architect the vision of what I want to accomplish. I leverage a coding agent to help me do the heavy lifting of the implementation and then I'm the reviewer to make sure that I'm staying on track and I get the result that I want to see as an outcome and then I do it all over again.

So fundamentally changing the way that you think about building. And at the beginning of 2026 I went all in on agentic software development. So what does that mean? That means I was able to write 200,000 lines of code for the latest product release.

Now to put that in perspective when all I did was write software in 2021 when I was building sensible AI forecast I wrote 70,000 lines of code for the entire year. So to put that in perspective that is a 30x productivity gain.

fundamentally game changing. And now as we enter the back half of the year just as we've now seen the agentic capabilities fundamentally transform the world of software and engineering that is now going to come for finance.

And now it's time for finance to have its own 2, 5, 10, 20, maybe even 30 productivity output gain. But the reality is for finance teams it's not just a flip of a switch and you achieve that type of outcome.

It comes down to I've got to think about the change management. I need to think about am I leveraging the latest and greatest models? Are those contextualized to the financial information and the business processes that I go through as a finance user? And that is exactly why we exist here at OneStream.

We're here to help insulate you from the pace of innovation, from all the new latest model releases and drops, while also codifying the AI capabilities directly into the business processes that your teams do each and every day.

So what does that mean? That means for you and your team, right, you get to be an amplifier, a superhero, and you get to set the new pace for how finance needs to run in the agentic finance era. So we've been in the game here at OneStream building AI systems for a long time, nearly a decade.

We didn't wake up when ChatGPT was announced in 2022 and get started. We've been building for a long time. Now, today I'm going to take you on the extension of that journey, right, and we're going to go through four key chapters together.

So I'm going to take you through Sensible AI Studio, which is all about giving you AI capabilities in the existing products and workflows that you're used to using on OneStream. Number two, we're going to hit on Sensible AI Forecast, how that is continuing to redefine the way you think about doing planning and forecasting at your organization.

And then number three, we're going to introduce you to your digital finance-focused teammates and what they can do for you. And then last but not least, we're going to show you how our agentic capabilities can meet you exactly where your teams want to work with our agentic layer.

So let's start with Sensible AI Studio. So last year, at this conference, very similar to this, we announced the general availability of Sensible AI Studio. And since then, it's empowered our developers, our implementers, our partners to build unique and innovative workflows with AI on the platform into the business processes that matter most.

And that's led to what you saw a brief stint of earlier, our narrative analysis capability, and it's even allowed, actually, our own development teams to build these turnkey solutions, right? And so one of those turnkey solutions is the narrative analysis capability that you saw earlier.

So what is the narrative analysis capability about? It allows you and your team to seamlessly summarize hundreds to thousands of comments that your teams are generating as part of the month-on-close process and pull out the key nuggets of information that matter most for decisioning.

Number two is AI account reconciliations. And AI account reconciliations is all about reducing cycle time and mitigating risks for those preparers, their approvers, and the auditors that go through that loop every single month.

And then last but not least is the operational data chat, which gives you instantaneous access to operational insight, the operational information that you decide to bring in to one stream in natural language.

So today we're continuing to double down on our sensible AI studio portfolio, and when we think about that, we are incredibly excited to announce the general availability of our sensible AI clustering analysis solution.

So the reality is for most teams out there, right, you either benchmark by region or by org chart. The reality is that's why it's so difficult to actually have benchmarking really change and lead to a decision for the organization.

And the reason for that is you're not really ever comparing apples to apples. So the whole point of sensible AI clustering analysis is to completely change that. And so sensible AI clustering analysis allows you to define what we call intelligent peer groups that allow you to bucket your entities by the actual operational and performance potential.

And what's interesting, you know, if you do that, if you're a retailer, that might mean that you're bucketing your store, your entities, your stores, you know, by parking lot size, shelf space, population density, distance to nearest competitor.

If you're a manufacturer, know, that might mean I'm clustering and grouping my and getting my intelligent peer groups by plant capacity, by production line count, skew count, and distance to suppliers.

And what's really interesting is once you truly have that apples to apples comparison for the very first time, it unlocks three incredibly powerful workflows for you within the solution. So number one is benchmarking.

This is all about allowing you to identify actionable spending gaps. So not, hey, this region underperforms, it gets into the nitty-gritty detail to be able to tell you, you know, hey, this store is overspending on SG&A relative to its peer groups, and here's exactly what we can do about it, and this is what I'd recommend doing, right? That's the level of detail that we can start to get to with sensible AI clustering analysis.

Workflow number two is drift analysis. Think of this as your early warning performance detection system. So this means that for every single entity that you have inside of your organization, you can find the ones that are trending away from their peer group in the wrong direction.

from a performance standpoint. And flag those on a weekly basis so that you can catch and take action, not in the quarterly business review and not in the annual review. And then last but not least is the peer group aware analytics.

So this is really about giving you the ability to automate the reviews. So these are peer aware scorecards by entity and allows you to start your reviews with the analysis and not the data wrangling exercise that typically goes on with it.

So at the end of the day, why does this really matter? This is all about smarter capital allocation. So the next time a leader in your organization needs to choose, you know, if you're a retailer, which stores to expand, which to renovate, which to shut down, or which ones to acquire, clustering analysis is there to tell them where the dollars are actually going to move the needle without necessarily hurting growth investment.

Right? That's what we're after. So if you're curious to learn more, we've got the opportunity to, you know, we've got the breakout session where you're going to be able to come and learn what it looks like to go through an implementation, what the value proposition looks like through the eyes of a, through a customer.

So I highly encourage you to come join us at this session with MB2 Dental. But to give you a little bit more of a taste before we wrap, we've got a fantastic demonstration that we're going to be here to take you through over the next five minutes.

So let's roll the demonstration. Sensible AI clustering analysis. Let's assume I'm an FBA lead at a manufacturer and retailer of golf clubs and equipment. Our board just kicked off the 2026 planning cycle and has asked me to find another 100 basis points of operating margin without cutting growth investment.

Within one stream, every regional location gets benchmarked against its regional average, south against south, west against west. But here's the problem with that. The stores within a single region don't actually operate the same way.

Footprint size, distance to the nearest competitor, etc. are all over the map, even within the same region. Take these two stores, for example. Both in our south region, one is 30,000 square feet with a competitor across the street.

The other is 6,000 square feet with no competitor for 12 miles. They have the same regional target, but those two stores are comparable on anything that drives costs. Now let's watch what happens when we cluster these stores by how they actually operate.

Three real peer groups emerge from the data stores and up ground with their operational twins. Not by where they are in a map, but by how they run. Every feature we use to cluster footprint, competitive isolation, density, product mix was chosen specifically because it drives performance.

Let's zoom in to one cluster, high density, large apparel stores. They are all operationally similar, but this dashed ring inside the cluster marks the top quartile performance in that peer group. How we define that performance matters.

Performance here is the blend of three commercial metrics. Revenue per square foot, revenue per visitor, and gross margin. Better operators will naturally rise to the top. In this store right here, bottom of the cluster on performance runs at 29%, almost double its peers.

Just by closing that gap by 50% means a $935,000 opportunity. If you repeat that process across every store and every cluster, we'll find approximately a $10 million saving opportunity in SG&A across the business.

Let me show you what this will look like inside OneString. Let's start by looking at performance scores. This is how we tell clustering analysis what makes one store or one group better than another. We can set our performance scores by just sliding up and down these sliders.

SG&A is intentionally not in that definition. This is purely how well each store monetizes its footprint, converts its traffic, and holds its margin. Now let's look at the learnings this enables inside a benchmarking workflow.

We pre-built and ran this workflow configured with the accounts for our OneStreamCube and performance score we just looked at. So here's my answer to the board. Closing just the gap to the third quartile of top performers, the most conservative opportunity is a potential savings of $6.4 million just on this one payroll account.

So our EDEO3 is the headline here. It's a dense market large apparel store, and it has a total opportunity identified of $2.6 million. And there is one thing that most benchmarking tools leave out. For every account where this store has a gap, the system has already drafted plain English guidance for how to close it.

For something like office supplies, it says that a vendor consolidation play that other high and density large apparel stores have already run could work for you. This means that my controller doesn't start with just a blank page.

They start with a draft that they can challenge or run with. For a specific store, a specific account, they get my specific recommended action, and a human will still own the call. The system doesn't post the entry.

It gives the team a starting point. So back to the board's question. Another 100 basis points of margin for 2026. From this single workflow against one cost area, I have millions of dollars that I can defend with action plans for every store and every account.

And this is just one of the three workflows available within clustering analysis. So there's three things to take away here. One, this analysis ran in minutes, not months. Two, it's finance owned. That means no data science team and no custom build.

And three, every dollar and every opportunity ties back to a specific entity with a defensible action. From regional averages to operational truth, benchmarks the decisions. That's smarter capital allocation.

Applause So some pretty powerful capabilities there. Again, that's just one of the three key workflows. If you're curious to learn more, we've got fantastic breakout sessions and demo pods for you. But keep in mind, we're doing this at enterprise scale to deliver you the trust, transparency, and governance that you expect out of a solution like this.

Right? And best of all, you can get started with this today as this is now generally available. So when you think about that, as you leave Splash, this gives you and your team the opportunity to get started.

And just within six to eight weeks, you could be live with sensible AI clustering analysis, entering your next budget cycle, your next annual operating plan cycle, to have these types of insights at your team's disposal.

All right. Let's switch gears to chapter two here. So when we think about enterprise scale, let's talk about sensible AI forecast and planning and forecasting. And sensible AI forecast has been out in the market for roughly about five years now.

And it's been serving some of the largest organizations of the world across, you know, manufacturing, retailers, services-based organizations, financial services. And it's also been able to touch a wide variety of planning use cases, whether that's, you know, workforce planning, operational planning, financial, and demand.

All right. So a lot of opportunity when you think about sensible AI forecast. Now, across the board, we've consistently seen, on average, a 25% accuracy improvement for our customers. At the same time, we're seeing, on average, an 80% faster cycle of planning and forecasting.

So what does that really mean? What does that unlock for you? It allows your teams to, rather than forecast, you know, plan and forecast once a year or once a quarter, you now get to do it once a month and once a week, right? Fundamentally game-changing to allow you to move and keep pace with the demands of the organization.

So there's no better way to illustrate the power of sensible AI forecasts than hearing directly from a customer like Amersports. Let's hear their story. Please welcome, from Amersports, Rick Martel, and from PWC, Leonardo DiBiassi.

Good afternoon. I'm Leonardo DiBiassi, One Stream Alliance lead with PWC, but most of you know me like the Italian guy with the scarf. And actually, if you were guessing, I have the scarf in Florida as well.

No worries. But we are not here to talk about my scarf collection. We are here to talk about an incredible transformation journey that moved from the now of the finance excellence to the next of the innovation that the sensible AI is bringing.

We are talking here, we are going to talk about Amersports. How many of you know about Amersports? No many. Rick, do you have any idea? You know, Leo, I think they don't know us as Amersports. I think they may know some of our brands, though.

So let's roll the footage. We'll be right back. Hello, everybody. I'm Rick Martell, the Director of Financial and Planning at Amersports. I've had the pleasure of working in the sporting goods industry and retail for over 15 years.

I've worked in massive finance organizations, and I've worked in finance organizations where I was the whole organization. So when Amersports called about two years ago, I recognized the opportunity and challenge immediately.

Imagine running a $6 billion portfolio of world-class sporting brands, each with its own identity, its own culture, and its own way of doing things. That's Amersports, essentially. And for a long time, that was also the challenge.

We weren't one company. We were many companies that happened to share one owner. It's an incredible portfolio. Now, managing that diversity requires a sophisticated backbone, and that's when we turned to Leo.

I have to say, every time that I see that video, I feel so pumped up. I want to start running, but I cannot now. This incredible portfolio of brands needed a very strong backbone for financials. Think about people that were from Vancouver to Shanghai through Chicago and Helsinki.

You have to monitor everybody from New York. With PwC, we are used to big transformation, but what we were facing in that moment that we started the engagement was like more, I could call it, a Pokemon card collection, but instead of cards, were tools and license costs.

We had Oracle FCCS just implemented that was not giving the right answers to the new CFO. There were one single tool with the SAP, Oracle, Excel for planning in each of the different brands. There was an ongoing phase zero of an S4 HANA for just one region, and there was a possible central finance project to start.

It took me 15 minutes, honestly, to understand what one thing could do and save in terms of money and time for Amersports. Two weeks later, we were in New York with the CFO that told us, listening in a great way, we have one finance goal.

Bring me this. And five months later, after they stopped the central finance project, they paused the S4 HANA design. We were live already with consolidation. But what was coming next was the most exciting things, and that is when Rick came to the project.

That's right. So essentially, when Leo came on board, we already had our consolidation engine. They brought it to us here using OneStream consolidation, and that was our single source of the truth for financial reporting.

It was we had multiple ERPs floating around, and we had one trusted output through OneStream. It gave us the foundation, but we knew that we had to speak the language of finance. So we essentially asked every brand, geography, and channel out there, what if the organization had one language for financial planning? We brought finance leaders together in person for the first time.

Across the world, we called it the Design Council. Really, the first time they have ever been in the same room before from brands that had historically operated independently. And together, we defined planning requirements, we fought over hierarchies, but we agreed ultimately on how to performance the business as one.

We think of our planning architecture essentially as a wedding cake. At the top, leadership has visibility into the highest level, making fast, confident decisions. Below that, connected layers of detailed operational planning that fed directly into the view.

Every tier was essentially informed. Every tier is connected. No layer flying blind. OneStream was our key enabler for this, and the collaboration was the breakthrough. The planning project was ongoing.

We have all these people from all around the globe talking each other finally the same language, talking about something that was coming. But we realized that there was a need of speed. There was a need of give me value right now.

So we identified which one is the brand that is more in this need, which one is the process that needs, because it's very high value, but time-consuming, where we actually can do something bigger. And while the planning project was ongoing, we started the Sensible AI, a Sensible AI project that actually was in eight weeks bringing back to that specific brand something big.

What was your experience? That's right. So like Leo said, it was only an eight-week rollout essentially for Sensible AI, and it really made us change the way that we thought about doing things. AI became our first reviewer, and before a finance partner walks into the room for a business conversation, the model has already flagged anomalies, surface trends, and generated the first draft of the narrative.

We essentially enabled our organization to speak the business language in real time. So accuracy gains, time savings, and our finance pros were freed up to do the things they essentially were brought on to do, which is challenge the status quo and build relationships to drive the strategy.

So I know everybody here is stressed on bringing AI into their business. I was too. I think that's why they invited me. But honestly, after eight weeks with Sensible AI, this pilot really made the team comfortable with it.

We know that we had a one data model, and essentially we could trust what the AI was built off of. So finally, if you take one thing from the stage today, it's that your tools can only go as far as your team.

So we didn't win just because of this fantastic technology that we're celebrating today, but we won because we brought people along the journey. We gave them a seat at the table essentially before it was even built.

With OneStream, we are enabling the transformation. But bringing the people together, bringing the leadership that was engaged with us and identify where Sensible AI was creating the value right away was the key.

We were lucky because every transformation can be successful or not based on your ability to challenge the status quo. Apply the critical thinking on what you are doing. Don't be scared of starting something if you didn't have finished something before.

If you finish your planning process and it's 100% ready, you are probably late. For this reason, I really would like to thank you, Rick, for your leadership and your ability to listen, to bring the value that OneStream is creating for Amersport and for everybody that is using OneStream.

Thank you very much. Thank you. Thank you. All right. Rick, Leo, thank you so much. That's exactly what it looks like when you bring the power of the platform, Sensible AI together to turn finance into a strategic driver.

for the business. Now, this is the first time where we've had so many product announcements for Sensible AI Forecast that we can't actually squeeze it all into the main stage here. And so I highly encourage you to come and join us at our technical keynote where we're going to show you how you can even accelerate even faster on your time to value with Sensible AI Forecast, as well as learn from more customers and, you know, the implementation methodology, the, you know, the change management through some of our other great breakout sessions.

So, with that being said, I want to move on to our next key focal area, which is the agentic finance era. Now, at last year, at Splash, we announced the private preview release of your very first set of finance-focused digital teammates.

Into late 2025, we were able to rapidly work with a variety of customers to capture feedback and make sure it found its way into these agents. Let's take a look at what our Sensible AI agent lineup looks like today.

So, number one, I want you to think of our Sensible AI search agent as a one-stream expert in your pocket. And it's a one-stream expert in your pocket because it's read the 2,000 pages of platform documentation that we know your teams have not read, as well as the solution guides, the, you know, the world-class books put together by the top 1% of one-stream architects.

And because of that, it's led to the ability for us to have a slide-out panel in the platform that can virtually answer any question that your team thinks of about the one-stream platform. So, what does that mean? That means if I'm an end user and I forget how to upload my latest trial balance as part of my upcoming workflow, right, search has your back.

If you're a power user who forgets how to write a working capital ratio in one-stream syntax, right, search is there to help you with that. And it doesn't just stop at what we have put in search, right? We allow you to bring your own informational assets.

That means your accounting guides, your financial onboarding documents, the implementation documents, the enablement documents that your partners have built for you. That can help even further curate and tailor your experience with search specifically to your organization, your one-stream instance.

So, this is all about empowering every user in the one-stream platform to have information at the snap of a finger, right? And that means we're compounding time savings from seconds to minutes, minutes to hours, hours to days, days to weeks, and weeks to months.

Next up, we have finance analyst. And finance analyst is all about making every single end user in your organization as capable as the top 1% of power users across all of one stream. And so much of what finance individuals are focused on doing is, number one, pulling ad hoc, doing some sort of ad hoc analysis, on-the-fly analysis to find insights for the CFO, for, you know, the chief accounting officer, any, you know, other strategic business partner inside of the organization to help inform a decision.

Right? And number two is conducting workflows, the same workflow month over month, usually against the same set of chart of accounts, entities, regions, hierarchies. And that is exactly why we built finance analyst.

Right? Finance analyst fundamentally understands your specific one stream financial model. It understands that you decided to put, you know, the product dimension in user-defined dimension number one.

It understands that you put region in UD2. Right? It understands your legal entity hierarchies, your planning and forecasting hierarchies. And with that, that now allows finance analysts to give you instantaneous access through natural language, through our slide-out panel, access to your financial information in seconds.

Right? And that's ad hoc narrative reports, and it's even the existing reports, the cube views and capabilities that your team has taken the time to set up. So that's number one. But number two, in our latest release of finance analyst, it now gives you the ability to have what we call analysis automation.

Right? And this is all about allowing you to set up rerunnable workflows, allows your teams to establish highly curated plans for the type of analysis that you want done, whether it's variance, trend, flux, any type of analysis that you can think of, and set that up and deploy hundreds of virtual finance analysts at your company to uncover and come back with narrative-ready reports that your team can leverage behind a schedule.

Right? You can queue these up at the end of your, you know, close process. You can set them up on a calendar-based event schedule. And so ultimately, gives you a fundamentally different way to think about doing your analysis inside of the office of finance.

Right? Your analysis starts with analysis, right? Not the data wrangling. And so at the end of the day, right, it's great that we can return this analysis to you, but it wouldn't matter if you couldn't trust the numbers.

Right? And that's why in every single finance analyst plan and report, you get back an exact drill back, a hyperlink, back to the exact cell that finance analysts pulled from so you know exactly where the numbers are coming from.

Number three, deep analysis. Right? We all know that scanning high volumes of customer contracts for, or, you know, supply contracts or order schedules, customer revenue contracts, and looking for things like total contract value or different types of rebates or early termination rights that we need to be, we need to be thinking about as a finance team.

Right? Effectively, what we're talking about here is the classification of documents and pulling out structured insights that we can act on. Right? That is exactly why we built deep analysis. And it allows you, just like finance analysts, you can set up reoccurring workflows.

So the next time you've got the next batch of, you know, 100 plus contracts that you need to go through, the deep analysis will exhaustively search word for word, read every single contract and pull out that informational insight for you.

And then that way, you're, again, your analysis starts with not reading contracts but with the structured insights that you told it ahead of time to pull out for you. So fundamentally game changing and gives you back so much time.

Now, we are fortunate enough to partner with Cox Enterprises, one of our customers, through our private preview program. And they help shape the direction of all of these three agents, right? Let's hear about their story and how sensible AI agents are making a real difference within their office of finance.

Please welcome Cox Enterprises, AVP of Finance Solutions Delivery, Allison Adrian. Hi, everyone. I am so excited to be here today to share with you our journey. It's very fitting because it actually started at Splash last year where we began conversations about being part of the private preview.

But before we move into finance or talk about finance or AI, I want to start with innovation because at Cox, innovation doesn't live in a lab or a tool. It starts with the business. This week, you'll see that firsthand at the Innovation Hall where we're showcasing Cox Farms.

Cox Farms is the largest greenhouse operator in North America, using high-tech indoor agriculture to grow fresh food closer to where people live. It's a great example of how Cox invests in innovation to solve real-world problems like sustainability, food security, and supply chain resilience.

So in case you haven't heard of Cox, it's a family-owned Atlanta-based enterprise spanning communications, automotive, media, and sustainability. And while our businesses look different on the surface, what connects them is long-term thinking, discipline growth, and practical innovation.

Finance plays a key role in enabling that, not just reporting the results, but supporting better decisions across the enterprise. Like many large organizations, our finance environment grew organically.

Multiple divisions, multiple systems, many, many manual processes, which meant time spent reconciling data instead of explaining it. We knew that if Cox wanted to scale innovation, finance had to scale with it.

That meant fixing the foundation first. One stream gave us a unified platform and a single source of truth. We started with consolidations and then expanded into planning and reporting. We created consistency and trust in our data.

And today, hundreds of users across accounting, FP&A, tax, and treasury work from that same foundation, which made AI adoption realistic and responsible. So you might ask, how did we approach AI? We didn't ask where we could deploy AI the fastest.

We looked where we could unlock the most value and build momentum. And that's why we started with accounting, not FP&A. Predictable workflows, high volume, and clear policies made it the right place to start.

Improve value and confidence before scaling it further. So we had several use cases. I'm going to give you an example in each of the agents. So finance analysts proved fast, reliable answers using our trusted One Stream data, which reduced the back and forth and allowed our teams to really focus on analysis of data versus the retrieval of data.

Search enables self-service across policies and how-to guides for quick answers, which reduce dependency on our system administrators. And deep analysis scans revenue contracts at scale, pulling out the key terms specific to our different users and allowing the teams to really make decisions rather than the manual review.

And with any new capability you learn along the way, and we had three main lessons learned. Configurability is powerful, but requires discipline, especially for AI. Iterative delivery beats Big Bang, and change management is just as important as the technology itself.

One Stream is highly configurable and flexible, which is great, except when training AI. Context and naming conventions really matter. So we learned quickly that refining business context, example questions, and security setup in partnership with our users was essential.

And so use cases improved materially throughout UAT, previews, and the phased approach rather than a one-time design. Lastly, clear communications, role-based training, and early life support were critical to adoption.

Treat the AI agents like a new capability, not just a new feature, and plan accordingly. By treating AI as a new capability with enablement, guardrails, and a phased rollout, it helped us gain momentum and adoption.

So what's next, you might ask? As a private preview partner, Cox will continue to influence the roadmap direction, ensuring sensible AI agents evolve in ways that are practical, secure, and purpose-built for enterprise finance.

We asked OneStream in the beginning to move finance analysts into Excel, because that's where our users are, and by meeting them, they grew comfortable and more confident. But where we're headed next is orchestration.

Today, OneStream helps us see that a variance exists, but what excites us is answering why it happened. With MCP coming soon, we see OneStream connecting securely to transactional details in systems like Dynamics and Workday, allowing finance teams to move from identifying an issue to truly understanding them, and all without leaving the platform.

So while we're still early in our journey, we anticipate thousands and thousands of hours saved across each of our functional areas. innovation at Cox is practical and purposeful. AI isn't about replacing people.

It's about multiplying expertise. And with a strong foundation, thoughtful change management, and the right starting points, finance becomes a catalyst for innovation and not a constraint. Thank you for listening to our journey, and thank you to Cox.

Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. All right. Thank you, Allison. What a transformational story that highlights the power of sensible AI agents.

And before we move on, she did a great job alluding to where we're going with the agentic layer. But as you might have noticed, we still have one card left to turn. And that's because I'm incredibly excited to announce our fourth agent to the lineup, sensible AI forecast agent.

So this is all about us laying a agentic capability over the entire product surface of sensible AI forecast. That means over the data, the processes, the project configurations, the workflows, as well as the transparency layer that we have built into the product.

So what does that mean if you're a, you know, end user? It fundamentally changes the way you get to interact with the product, right? It means that I get to ask in natural language behind the slide-out panel or directly inside a sensible AI forecast, why does my forecast look the way that it does? Why do I see a big spike in April for this particular region, you know, product, or whatever level of dimensionality you're focused on, right? And sensible AI forecast agent is able to take your question, contextualize it, and then turn it into a narrative-ready report.

Right? But grounded in the transparency that comes as a first-class capability within the product. That means the, that gives you the ability to ultimately see what macroeconomic indicators are driving your forecast higher or lower.

What sales promotions, what supply chain shocks, right? Any of the features and indicators that you provided sensible AI forecast, you get to see that in a narrative-ready report. Now, the best of all, sensible AI forecast agent can give you inline graphs and charts.

It can actually give you full-blown sensible AI forecast dashboards returned in the conversation chat as well, based off the type of question that you ask. So, really meeting you with exactly the language that you speak as a finance user and giving those capabilities at the snap of a finger.

All right, so these are native OneStream agents, right? These are, and hopefully what you can see here is we're moving from them just being a chatbot thought partner, which gives immense value, but also moving them towards task-enabled workers that can truly unlock the next scale and efficiency for your organization, right? You see that with the scheduling capabilities of deep analysis, with the scheduling capabilities of finance analysts, so you can deploy hundreds of instances of these capabilities at your team's fingertips.

And they're purpose-built to exist inside of the workflows that you work in each and every day inside of OneStream. So, we've hit on our native agents. Before we go to the agentic layer specifically, I want to recognize, I think, something that we're all feeling, which there's been a radical change in user experience, is expectations.

Right? I felt this working now with, you know, Microsoft Copilot, Claude Cowork, ChatGPT, Google Gemini, and what we used to tolerate as a user was, hey, if I needed to get an insight, I might actually have to go to, you know, three different dashboards, and I might have to go into Excel, into an ERP, into some other system to give the full package to, you know, a CFO or, you know, another constituent within the business to make a decision.

And at the end of the day, with the advent of these external agents, it's fundamentally changed the way that we think about interacting with software. Right? Now I expect, I think we all are starting to expect, that as an end user, I want to be shown the result in the way that I want to see it, in the language that I speak, and you've got 30 seconds to give me the answer.

Right? That is where we're moving, that's where we're heading as we interact with software. So, what can you do about it? Right? As an end user, one of your opportunities is to actually put an agent between yourself and the data.

Right? And there are so many use cases this unlocks. Right? Immense productivity at a personal, a team, and at an organizational level. But the reality is when you sit inside of the office of finance, there's actually another gap that emerges when you just do that.

Right? And that's the governance gap. Right? And we know within the office of finance that numbers cannot be wrong. So, what does that governance gap actually look like? Right? The questions that naturally start to emerge are the ones that are maybe a little bit less obvious.

Right? How do I know that an agent is going to be working against my actual source of truth information? Or how do I know that an external agent is going to abide by my intercompany relationships? Or how do I know that when I'm talking about closed consolidation that I wanted to aggregate up my legal entity hierarchies, not my planning and forecasting hierarchies? Right? Or maybe I'm, you know, heavily into M&A as an organization.

How do I know that it's going to be able to abide by my changing ownership structures that we're always dealing with? Right? Those non-obvious but critical to actually getting the right number that stuff really matters.

So, that's why we're extending the workflows, the processes, the financial intelligence outside the four walls of OneStream. Today, as Tom mentioned, we're incredibly excited to announce OneStream's agentic layer.

Now, now, whether your teams are working in Copilot, ChatGPT, Claude Cowork, Excel, right, every insight, every action, and every result is grounded in OneStream's financial intelligence. That means you get to have any agent you choose and have every single answer be governed.

So, that's what it means to truly have agents your way. So, now, your teams get to work with the tools that they prefer while you get to maintain complete control of the truth. That's the power of the OneStream sensible AI agentic layer.

Now, I can think of no better way to continue this keynote than to bring out one of the leaders in the agentic era and OneStream's strategic partner, Microsoft. Please welcome Microsoft CTO, Global Partner Solutions, Tony Serma to the stage.

Thank you so much. Thank you so much for being here, Tony. And when we think of Microsoft, you're on the frontier of AI adoption in the enterprise. And you're not only delivering the tools, but you've spent considerable time in research, you know, understanding the emerging AI operating model for business.

So, from your vantage point, from what you see, how is AI reshaping expectations within the finance function? Yeah, first of all, thank you for having me. Thank you for being a partner with Microsoft.

Thank you all for being here. Possibly like my team, your team might be worried you'd be sneaking off to a galaxy not so far away. So, I'm thankful that you all are staying here with us. So, to your actual question, what I want to say is, we've worked with a study that's based upon thousands of enterprises and looked at what's happening with AI, Agentic, everything that's going on, and we found a couple of things.

First, they modeled this in a quadrant, in the upper right-hand quadrant, as always is, is called frontier firms. And what was seen there is that there's three things that define the folks who are driving leadership internally and within their industry and getting the most results around adopting this wave of technology.

The first is that they're simultaneously bringing together organizational readiness and frameworks with their technical readiness and frameworks. So, that means it's not just about buying a technology using a technology, it's about how you align that with the business, and you've heard that so far throughout this keynote.

The second thing is specifically around readiness, looking at their data state, looking at their skills, looking at how they apply governance, all of that, and thinking about how you need to be ready for this transformation.

Much like the move from paper to a computer, or from an on-premises data center to a cloud, there's things you need to be ready and know about, and so it's those who really focus there. And the last thing is frontier firms, the ones that are the most successful, are not the ones that are the most experimental, it's the ones who are the most intentional.

And intention in this case really means having that readiness, everything I said. It also means looking at this through an eye of how are you going to get the business value? How are you going to see ROI? How can you analyze, predict, see what you want to see come out of that, pick the right choices, get that value early and often, and then evolve from there.

And one of the things that I think is so important for this audience, what I just described, sounds like the superpowers of a finance department, of folks in the CFO or other audiences, where you need to think about how do you make the right decisions, how do you inform that with your data, how do you see an ROI, a clear path to value when you leverage this technology.

So I think there's an opportunity to advance everybody's enterprise, but also an opportunity for finance to play a really strong role there. Absolutely. And I think you hit on one key element there, the technical readiness being super important.

and it seems that, you know, finance would need help in defining and executing an AI strategy, you know, both within the function and across the enterprise, right? And so how do you see AI reshaping the partnership that might exist today between, you know, the IT team and the office of finance? Yeah, I think that's exactly the way to think about it is think about the partnership between finance and IT as like the physics or the operating model for the enterprise.

Because if you've thought about what I just said a moment ago, you need organizational and technical, that means your data state, your security, all of those technical aspects need to be modernized, need to be leveraged by agents and other such things.

And remember, AI is going to be like a robot with a flashlight. It's not going to see stuff it's not supposed to. It's going to see the stuff that you configured it to see. And so that means it's going to be very important to have the technical data governance security, all of those aspects inside of there, so you can get that.

At the same time, as you heard earlier, AI without data is a very eloquent guess. And so you need the data and the context that's going to come into that. Finance is a great way to drive that. Also think about governance, think about risk, think about all that other analysis.

So again, together, I think this becomes that operating model. And one last advantage of what's happening right now with this technology transformation, just like the IT departments worried less about keeping servers powered and turned on when they move from on-premises to the cloud, this is allowing, this wave of agentic is allowing you all in finance and IT to, again, up-level from those tasks that you do have to deliver to focus more strategic and to have that time to drive the enterprise forward.

So simultaneously, we have the opportunity where it's the right two organizations, but also the technology that's enabling the right capabilities in them as well. Absolutely. I think to that same point, I think OneStream and Microsoft have a key role to play there for you all out there in the audience.

And when I think about that, OneStream and Microsoft, you guys are one of our, you guys are our most strategic partner to OneStream and a longstanding partnership with a common mission to deliver the innovation that empowers finance and IT to accelerate and achieve exponential value.

So for those that don't know, OneStream is entirely built on the Microsoft stack from the .NET runtime to the Azure databases, the Azure compute, you guys are critical to us. And as you heard from Jeremy today, the Office 365 add-in is another huge plus as we move towards continued integration at the application layer.

So when you think about that, and I would love to hear your view on Microsoft OneStream partnership and the joint value we're able to collectively deliver to customers. Yeah, as I said at the start, thank you, thank you for the partnership, but I think more importantly, we know that we are a partner-powered company.

And so we know that the value of our platform is going to be realized best when we can work with our partners and bring the domain expertise and what you all need. It also means that if you're a joint customer of ours, that their solution, their capabilities that we work together to build are running in the same environment, are running in the same platform that drives intelligence, choice, and trust, does that at enterprise scale, that if you're on the IT side of the house, you have consistent ways of looking at security and other aspects of operationalizing that environment, it also means that you can take advantage of looking at the data that's between any solution you're running on our platform and bringing that together.

So there's a lot of better together is what we sense there. And not just on the technical side. You're a great partner in terms of our marketplace and the ability to procure and transact and even leverage the usage of this platform, this technology, through a commitment you as a customer may have to Microsoft and you're something called a Mac.

And then overall, what I would just say is we have a great partnership building solutions, building those differentiated capabilities. I know you know this, but I don't know if everybody in the audience knows that you were actually voted, awarded, recognized, if you will, as the Microsoft Software Development Company Partner of the Year in the Americas, the organization that I'm part of.

Absolutely. Thank you. That's incredible. Yeah, I appreciate that. As we think about, you know, we hit on some of the infrastructure and scale and some of the application layer, and we're continuing to innovate more at the application layer with you guys as well, is one of the most exciting announcements here at Splash is how we're incorporating one stream sensible AI agents within the Microsoft Agent 365 agentic framework.

Can you impact that a little bit for us as well? Yeah, so as you heard and as you saw today with those little agents on the Pokemon cards, which I loved, I'm clearly a nerd. I also love Excel, by the way, so I feel very much at home.

But one of the things that we realize is that as more and more agents and more of these solutions are deployed, we have a product, we have an offering called Agent 365, because just like you've heard today, you're going to want observability.

You're going to want the ability to know what it's doing, what identity, what security frame that that's operating under. You're going to be able to discover either agents that you've acquired through great solutions like OneStream, or that might be being developed by your own team members, or even from other competitive platforms brought into your enterprise.

Overall, that's what Agent 365 does. It takes great specialized agents, like you see here today, and brings that broader environment so you can wrap the security, the governance, observability, all of that in there together.

And then we couple that also with all of our data capabilities and underneath there, another area that you're partnering with us greatly and in the future. Because we know, as I said earlier, data is key to the value of AI, and it's not just the data in one system, it's the data across systems.

So those two capabilities to manage, monitor, and observe what's happening in a controlled environment with your agents and empower them all with the proper data across multiple solutions, data sources, data types, those two areas together create sort of the two best value vectors to make AI do the promise that we're looking for together.

Yeah, absolutely. Yeah, and as we think about the, you know, just even further on the application layer, you know, with the Microsoft tools that you use each and every day out there in the audience, could you give a few examples of, you know, where OneStream sensible AI agents might show up for you, you know, and help solve some finance use cases.

Yeah, the great part is I'm actually going to say nothing you haven't heard already in this keynote. So obviously, you know, we know that you all work in Excel, we heard that. When you hear the phrase buckle up in Excel in the same breath during a conference, again, you know you're somewhere special.

And so we have that ability for those agents together to show up inside of Excel, where many of us work a lot during the day, but also in teams or other products you may be using for that ad hoc collaboration, for that question and answer capability you want to do.

And then also, as you've mentioned, within M365 Copilot, we see it's very important that as people use those productivity and cross-domain agents that really understand your enterprise, the files you might have in SharePoint and OneDrive and the communications in teams, being able to bring in that data and that agent capability from the platform creates an opportunity that you can tie that all together so that our whole key here is we, as we've heard today, we want to augment, we want to amplify, we want to put agents and AI in sort of the flow of human ambition, not something off to the side.

And so the ability to meet all of your users, all of our customers together, where they are and the tools they use, that's key to our philosophy and the partnership that we have. 100%. I couldn't agree more.

And in the meantime, right, as we look to wrap up here, if there's one message you'd want to leave finance leaders to walk away with about this partnership, about AI, what would it be? Yeah, so let's probably take it back to one of the first things I said.

Vic, this is a wave of transformation. You're seeing what one stream is going to do to help you go through and take advantage, leverage, and get the benefits of that wave of transformation. Microsoft certainly does that as well together with you.

But I think it's more than just being able to leverage and get the benefits of this wave of transformation. Together, I think we're creating the opportunity to take finance further as the leaders of that transformation.

So you can all drive the next opportunity, the next evolution, the next generation of whatever you do in the companies that you're part of. So take that leadership opportunity, leverage what we're bringing plus what you know about your business to really drive the future that we don't know what that is yet, but we're going to build that together.

Absolutely. Tony, thank you so much for being up here. Thank you, Microsoft, and I appreciate the time today. All right. All right. So we've spent a lot of time now talking about how agents can transform work inside of the platform, outside of the platform, within Microsoft, but with the consistent one stream financial intelligence, powering every agentic interaction to deliver the trust that you need.

Now, with that being said, let's actually see this in action. I'd like you to please welcome to the stage Charlie Numer, one of our key strategic leaders in the Sensible AI Agents Initiative, senior manager, and AI engineer.

Charlie, take it away. Thank you. Awesome. Thank you, Drew. Now let's hop in and take a look at our one stream agentic layer in action. For the sake of this demo, we're going to be focused on our CubeData MCP.

This new set of MCP tools now allows our third party agents like Claude, ChatGPT, Gemini, and Copilot to both search and execute existing one stream cube view reports, as well as have the ability to pull any slice of one stream cube data.

So let's hop in and ask Copilot a question. We can start here by asking, can you please pull my income statement actuals versus budget for North America equipment? As we ask this question, Copilot's going to use the native one stream tools to go through and search for all the relevant reports defined within the application.

Along the way, resolving any necessary inputs like North America equipment, mapping to our specific entity, and finally pulling the data directly into Copilot. And along the way, each of these individual data pulls flows through the one stream agentic layer, ensuring it follows your existing security and access model that you have defined.

As you can see here, we now have that report pulled directly into one stream. And now we'll hop over to Claude and take a look at another example. As we can see here, we pulled to have that same income statement report defined, and we now want to look at that large compensation variance.

We can now ask Claude, let's drill into our compensation variance to determine which cost center is driving it. Please include a chart along with the data. Now, similar to what we just saw with Copilot, Claude's going to begin reasoning over which tools to leverage for this specific question.

In this case, choosing to use our dynamic querying capabilities. The first tool you're going to see leveraged here is always this get application context. This ensures the agent pulls in all of the relevant information about your specific one stream application.

Things like your relevant fiscal year offset, your specific cubes, all that key information that the agent needs to then use the next tools properly, which it can then go through, search for your dimension members, traverse your metadata hierarchies, and then pull that targeted slice of one stream cube data.

As we see it finish up here, the agent will then start to generate us this highly rich and interactive visualization, in this case showing us which cost center is driving the variance. And as you can see here, the operations cost center is that largest driver, and we also get this nice summary along with the visualization.

This should start to show you what these third party agents are now capable of when directly powered by the one stream agentic layer. Now the ability to search and analyze your one stream cube data is not just limited to third party agents.

Our native finance analyst also has the same underlying set of tools and capabilities, except defined exactly within the one stream application. However, we've now taken things even a step further. With the next generation of finance analysts, businesses are now able to automate hundreds of analysis flows to execute in the background on their behalf, all with a focus on transparency and auditability.

Let's click in and take a look at a plan that we created to run a variance analysis on top of that same income statement report we saw earlier. As we enter in here, you can see you drop into this planning agent where users can then work iteratively to help build this highly accurate analysis flow.

And if we take a look at what's included here, you can see we start off with that high-level objective, going deeper into some of the key assumptions, and as we go deeper, following that same flow that we want the agent to go through, the dimensions to drill down, all that key information and detail needed for the agent to execute this analysis the same way each time.

We then have the ability to take this analysis and set it to run on the schedule. If we click in here, you can see for that same plan we just created, we have now set it to run on the first of each month at 8 a.m.

We can now click in and take a look at the generated report right there. And as you can see here, at the top we have that summary showing the core underlying cube level drivers. That were surfaced for this specific analysis.

And as we scroll down, you can see the process the agent went through. Starting with that top-level income statement, and depending where the variances were, going into some additional drill downs. In this case, starting with the account-level findings, going into a different operating drill down, and along the way, not only surfacing the charts, but also surfacing some underlying commentary.

And at any point, we can click on any of these cited sources to take us to the direct one-stream data pool that was used to generate that insight. This ensures users have that transparency and auditability into exactly where their numbers are coming from within OneStream.

Now, this should start to show you how OneStream is now allowing your finance teams to leverage agents your way. Thank you, and I'll pass it back to Drew. Thank you. Thank you. Thank you. Thank you. Thank you.

Thank you. Awesome. Great job, Charlie. And that hopefully, truly showcases you the power of sensible AI agents, and again, always being able to meet you where you want to work in any of the external agentic products, as well as directly inside of OneStream.

Now, I am here to promise you that we are on a mission to make sure that you always have trusted, secure, and purpose-built agents and production-grade AI systems that your teams can rely on each and every day.

Now, I highly encourage you to come and see us again at some of the great breakout sessions, the technical keynote. The technical keynote is going to be great for those that really want to learn the magic behind our agentic layer.

Federico Kaliski is going to go all into the detail of the open protocols, the model context protocol standard. And so those that are looking to roll out AI capabilities, their own agentic products in any of those external agentic products, you've got the ability to integrate the OneStream agentic layer into that.

Additionally, we want you to learn more from our customers. Right? We've got a ton of great breakout sessions going into the implementation, the value proposition, the value impact across all of our sensible AI products.

And then if you're curious to learn more about a particular product or feature, come see us in the innovation hall. We've got, you know, fantastic demo teams there ready to showcase you the latest and greatest of what you heard us talk about here today.

And we're even giving you the opportunity to actually test drive our sensible AI agent. So come join us, get hands on keyboard and experience it for yourself. Now, with that being said, I'd love to welcome Tom back up to wrap things up.

Thank you. All right. Well, I want to say what a great show, like I promised, but I do feel that I got robbed because I got up here to get you all worried about everything going faster and your agents are going to go rogue and give you the wrong answer.

And then they got to come up here and tell you, no, it's all okay. So today we've seen a lot, right? Not just new capabilities, but we've also got to see that there's really a new operating model. And it's all powered by our uniquely unified, infinitely extensible platform.

So I just want to take a minute here just to kind of clip through, you know, our core capabilities and really revamp and review what we talked about here. And that is we're investing in the core. We understand that you have to have reliable data.

We're here to give you operational depth, the ability to steer your business. And you can see just the major leaps that we've made in artificial intelligence. So as we continue going through this process, we can see that it's really the time for you to move forward, right? It's time to think about guiding the business and taking this to the next level.

Because what we see here is that you need to be able to stop reacting to change and start shaping it. So the question really is, AI, these AI impacts are coming. And it's for you, how quickly are you going to move? Because the future of finance is not something that you're going to be able to wait for.

It's something that you need to build. So let's go build this together with all these capabilities that we're bringing forward. Come and enjoy the Expo Center. Learn about these capabilities and see how you can bring it back to your organization.

We're really making it easy for you to consume these capabilities and deliver value for your organization. So thank you so much for your time. It's going to be a great splash. And we look forward to seeing you in all the different sessions and learning about how customers are getting value from our platform.

Thank you.