APAC | Domopalooza Showcase

Hello, everyone, and welcome to your Domopalooza showcase. My name is Brian Orloff, and it's a pleasure to spend time with you today. Domopalooza is Domo's annual user conference and product showcase in Salt Lake City, Utah, that happens in late March. And during this two-day conference, we announce new products, future vision, and we have amazing musical performances.

This year was OneRepublic and Busta Rhymes. And today, we have curated the best of the best from the two days into about a 60-minute session for you. We are living in exciting times, a moment where AI is no longer a future concept, but a real and transformative force, changing how every business operates, competes, and innovates. The organizations that succeed over the next few years won't simply be the ones with the most data.

They'll be the ones that can turn data into intelligent action faster than ever before. Today, we're going to show you how Domo helps bridge that gap, bringing together data, AI, automation, and human decision-making into one connected experience that empowers every person in your organization to move from insight to action in real time. Thanks for joining us today on this journey, and a look at what's already here and what's coming. But today, we're going to take you on that journey through the future of AI with Domo, exploring AI agents and MCP, the evolving world of semantics and analytics, and what it really means to be data and AI ready.

We'll also cover lots of quality of life improvements in many areas of the platform, like Magic ETL, governance, and secure distribution. And we'll also show you how organizations are unlocking AI value right now, and then wrap everything up together with the practical next steps for your own AI journey. Let me ask you a question. How many of you have used AI to inform a decision in the last 24 hours?

Okay. Now, how many of you would say you fully trusted the output? Mm-hmm. Now, I experienced this last weekend.

My wife and I hosted a poker night at our house, and like most of you would do, I jumped on my favorite AI tool to create a flyer, provide the rule, and to help me calculate the buy-in and the chips. This is what AI created for me. It's pretty impressive. One prompt, a couple of minutes to work on, on its own, and bang, it's done.

You got nice color schemes. You have the right chips, the colors, the denominations, and the buy-in. Looks great, right? Can anyone spot the error?

The total. It did not actually create the accurate total or the sum of all the chips. Now, I didn't realize this until after the fact. I'd already printed these, already distributed the chips, and hopefully my friends, it was a friendly family game, so hopefully they didn't think I was trying to cheat them out of chips, $250 worth.

So this is what happens. You need to not only use it, but you need to check the work and make sure it's accurate. And this is the gap that we're living in right now, the AI gap. This gap is the defining business challenge at this moment.

At the same time, true AI success does not occur as a one-off breakthrough. It starts with humans, your ideas, your context, and your understanding of what matters in your business. Then AI accelerates your processes and amplifies your imagination, surfacing new possibilities. This shift changes the role all of us play, and many of us will move from the role of knowledge workers who manage data to knowledge seekers who harness AI to uncover deeper insights and drive relentless innovation.

In this model, humans aren't just in the loop. They are the conductors orchestrating AI agents and tools to create outcomes greater than the sum of the parts. And as AI agents scale, organizations need a coordination and context layer, not just to automate tasks, but to improve decision using the collective knowledge of the business. That's what we call the intelligent enterprise.

And the foundation of the intelligent enterprise is Domo, connecting data, integrating systems, making data AI ready, and securely deploying AI where work gets done. Today, we continue on that journey. First, Domo has joined the Open Semantic Interchange. The OSI was founded by Snowflake so that disparate analytics, AI, and BI tools can operate on a single standard of semantic context, regardless of the platform.

Second, we are announcing the Domo MCP server. With Model Context Protocol, your preferred AI assistant, like Gemini, Claude Or ChatGPT can access the data, services, and tools in Domo while still respecting your established governance. Yes, very exciting, and I'll show you an example shortly. So what's next?

The future won't be won by the latest model or even access to the most data. It will be about using AI to connect people and data to action through context. It's about orchestrated intelligence, an ambient layer of intelligence that is connected through your unique business ontologies, forming a truly intelligent enterprise. It is coordination that will determine outcomes.

And as AI becomes core to how we work, the expectations for software interfaces are changing, moving from static dashboards, fixed workflows, and predefined paths as these AI tools are becoming the way you interact with information, as they become more familiar, more conversational, and seem to almost anticipate your needs. And Domo has always empowered organizations to harness their data, making the invisible visible and the complex intuitive, and we continue along that journey. And what if you can go farther? Combining the intuitive feel of your AI interfaces with a deep understanding of your business and the unique way you work.

So let me share the Domo vision. We call it Project Ambience. Ambience thoughtfully incorporates everything we have learned over the past 15 years, all the work on edging catalysts and the latest AI research. It learns how you work.

It remembers your patterns, your preferences, and the actions you take. And powering this next-level AI experience is something we believe is critical, your context layer, your data, your semantics, and your ontologies. And built on top of that context is something new, the intent engine, the core of Project Ambience. It connects your organization's data, workflows, documents, metrics, and institutional knowledge into a unified understanding of how your business operates.

What this means is every AI response is grounded in the context of your business, your role, and your goals. Because the real gap in AI today isn't capability, it's context. Let me show you how this materializes in work every day. Let's shift to a scenario that's incredibly real for a lot of organizations.

I'll step into the shoes of someone working in the supply chain at a global manufacturer. I get an alert like this. A shipment of a critical component is delayed. In most companies, that alert kicks off a scramble of emails, meetings, spreadsheets, and a lot of guesswork.

Instead, let's ask AI to show me the impact. It turns out the delayed part is used across multiple products, and the shortage will push production below required run rates within the next seven days, bringing operations to a halt in 13. If we do nothing, we risk missing delivery of a top-selling product for a major customer, and the revenue impact is significant. That level of AI insight is powerful and increasingly expected.

But what happens next is where it gets really interesting. Because it's grounded in the data and the operating reality of business, it not only answers my question but understands my intent and offers solutions. And while these look promising, you're all suspicious that AI is just telling me what I want to hear. But this is not some idle recommendation.

It's based on the activity and tribal knowledge of your business stored in the intent engine. So let's look at what happens under the hoods. This graph represents the semantic context and stored knowledge of your business, connecting the delayed shipment to the affected part, the products that rely on it, and ultimately, the metrics those products drive, like revenue and margin. If we want to understand how the AI arrived at this recommendation, we can trace the provenance behind that insight.

The AI evaluates approved suppliers, validates part availability and lead times, measures margin impact, and optimizes for the best financial outcome automatically. For example, it finds a supplier with a promising price, but then automatically eliminates them from consideration because of a previous discussion we've had about their quality control issues. Now, I'm going to ask the AI to act on this recommendation and place the order with an alternative supplier. Because it understands our workflows and past decisions, it automatically selects the right expedited process in Domo and submits that request.

It then notifies the right people, and every action and decision becomes part of the intent engine's memory for the future. Let's take a moment to dig into this. There are three layers of memory. First is episodic memory, the authoritative record of what happened.

This is every message, every action, tool call, and timestamp. Second is semantic memory, which captures what we know, validated facts, and reusable knowledge. And finally, procedural memory, which learns how work gets done, skills policies, and execution patterns that guide agent behavior and optimize workflows. Now, because the intent engine grows over time as it gathers additional context, even just a few weeks ago, the scenario might have followed a different flow.

That's the future we see. Domo as your foundation for agentic experiences, a platform where governance isn't an afterthought, it's at the core. You're empowered. Everyone is empowered to move from question to insight to action at unprecedented velocity.

As AI continues to evolve, Domo will be your partner as a coordinating fabric across data, agents, and governance, with humans composing the story, using AI to orchestrate, thinking bigger, and moving toward outcomes with confidence. That's the future we're building together. And let me bring you back to the present. Today in Domo, you can already talk to your data using natural language and ask questions against your trusted, governed, and secure information using Domo AI Chat.

But what if you can go a step farther? Asking Domo not only to generate intelligent insights, but to build applications and take action for you. Well, now you can with Domo App Catalyst. Let's have a look at this in action.

So Domopalooza has always involved a popular musical artist at the time. So when it comes to showcasing an example, the team decided to use data behind Billboard Hot 100 list. That's the data source in this example. In this case, let's ask App Catalyst to help me use this data to create my own Artist Explorer app.

What I love about this is that it asks intelligent follow-up questions to clarify my intent before generating a working app I can preview instantly. In minutes, we have filters, navigation, trends, and dynamic visualizations far beyond just opening a website. But the real power is this. Anyone can build generic apps.

What matters is building apps uniquely tailored to your business, your people, and things you care about most. In this case, we took the code behind the app and continued iterating with AI before publishing it, because the story we want to tell is about the artist who performed at Domopalooza using the Billboard data to bring that story to life. So we've added a button to go into Domopalooza mode. That's what we mean by purpose-built apps.

They may seem small until you realize how valuable it is to have something perfectly tailored for your business, your teams, and your workflows. And that makes building this in Domo different, is the app doesn't just inherit your data in context, it inherits your organization's governance and security rules, too. In this case, based on your Domopalooza attendance, while I might see all the years when you open the app, it would filter based on the artist that performed on the years you've attended. Pretty cool.

Domo App Catalyst is available today in public preview within your Domo instance, allowing you to start building AI-powered applications using natural language right now. When speaking to companies about AI, I often hear a common theme. "We've invested in AI, we've seen the demos, but we're still waiting for it to show up in real business workflows." Yes, AI can generate answers, but people still own the decisions and the outcomes. Boards and customers won't accept, "Well, the AI decided it." What organizations need is not just smarter models, but better systems, systems that connect trusted data, the right insights, and real business action, too.

That's what we mean by orchestration, and that's what we're building. It starts with the foundation, integrated, governed, AI-ready data. Without that, nothing else matters. On top of that sits a semantic layer, giving the AI the business context it needs through trusted definitions, models, and metrics.

From there, you activate intelligence through analytics, apps, agents, and workflow, all that governance built in from the start. And eventually, AI stops being a feature and becomes how work gets done. That's what it means to be AI-native, and I'd like to show you that vision in action. What's really exciting is that this isn't just future vision.

It's already happening today. Over the past 12 months since releasing Agent Catalyst at last year's Domopalooza, customers have built more than 200 AI-powered use cases across Domo, spanning sales forecasting, marketing optimization, executive reporting, supply chain automation, customer sentiment analysis, anomaly detection, HR onboarding, and many others. What we're seeing is organizations moving beyond static dashboards and beginning to deploy intelligent agents that can reason, automate workflows, and help teams make faster decisions at scale. What we're announcing here is a major evolution in how organizations operationalize AI with Domo, with three new capabilities.

First, the AI Library. The AI Library becomes your governed control center for managing trusted AI assets across the enterprise. Second is AI Toolkits. AI Toolkits allow you to package your business logic, workflow, prompts, and automation into reusable capabilities for every department.

And third, Agent Builder. With Agent Builder, teams can now create intelligent AI agents using natural language connected directly to live enterprise data and capable of taking action. Together, this moves Domo beyond dashboards and into a new era of intelligent business execution. Let's have a look at an example.

So here's an example of a webpage, an e-commerce webpage that sells books. So here we have featured books. We can look at different things. We can filter by different categories.

But I want to create an AI experience using chat. So let's go ahead and create a new toolkit. So here I am in Domo Toolkit Creator. I give it some descriptions.

Next, I can give it some tools. In this case, I want to give it the tool to talk to Domo documents or Domo file sets. And then I'll give it knowledge, and this is actually a document set. So we'll save this toolkit.

Once we save it, it also shows up as an MCP server. We'll come back to that in a moment. So after we have our toolkit, the next step is to create an agent. So to create a new agent, I give it a name, give it the model that I want to use, tell it the role, and give it specific instructions.

Next, I add the toolkits. So we can go ahead and turn on the toolkit we just created in the previous steps. Next, we can add knowledge, both structured as well as unstructured. And when we go to the UI settings, we can determine how it looks to the user, whether it's internal or, in this case, external on an e-commerce webpage.

I can give it existing questions, and I can hide the sources or make it available. And then I can also customize the color, in this case, going from white to black, to match our brand experience on the website. Once I save this, I then have my agent available, and I can embed it by copying the code, either a private link or a public link, and I copy and paste that onto our website. Now our AI chat on our e-commerce website becomes enabled, and now I can use natural language to ask and answer questions against that unstructured and/or structured data.

Pretty amazing, huh? So in a matter of minutes, we created a fully functional custom agent. Looking forward to what Agent Builder will soon become, it will be able to support agent-to-agent protocol, which allows Domo agents to be used in third-party systems. Or if you have a tool that's already best in class, you can integrate with Domo and have our agents leverage its functionality, while also limiting the amount of processing you're doing inside Domo.

You'll also soon be able to add multiple agents with their own toolkits by creating a parent agent with sub-agents. With this setup, you can govern an entire suite for your organizations. We are so excited about this full suite of new capabilities, and I hope you can see the value that Domo's AI Library will provide as you create, manage, and govern your toolkits and agents all from one location. Now, we just had a peek into agent-to-agent protocol via Model Context Protocol, or MCP within Domo And wouldn't it be nice if Domo could become a universal AI connector you could use anywhere?

Well, today, we're happy to announce that Domo is about to become a lot more powerful. Who's to say you can't take it with you? With our new Domo MCP server, virtually everything available to you in Domo will be available seamlessly and securely through Claude, ChatGPT, or wherever else you need it. And here's a little bonus.

We're talking more about more than just text. With Domo's MCP, you can also generate live visualizations, apps, forms, wizards, multi-step workflows right inside the chat. Let's have a look. So here we are in Claude Desktop.

The first thing I want to do is I can go into the connectors, and I'll show you that we have a new Domo MCP connector. And if I hit the configure button, we'll be able to see all the tools available within that to perform functions within Domo. Next, let's see what data I have access in Domo. So it's one natural language question, and as it's hitting Domo, it uses my credentials and comes back with data sets that I have access to.

Here, it's 86. Now, I can select one of those that I see that could be interesting, and in this case, I notice I have some Strava data. Great. Now, let's use that data to create a 90-day ride plan.

So now it's querying that data set, and now it has an understanding of what the content is, and it can actually create from that data set a highly visual and functional plan to ride for the next 90 days. Pretty compelling, huh? So that was using Claude Desktop to interrogate and create a visual experience directly from pulling data from Domo. Our vision at Domo has always been to bring data and people together through great user experiences and strong governance.

And that foundation is what makes AI so exciting. When passionate people, governed data, and trusted AI come together, real business outcomes happen. But to truly trust AI, you need more than powerful tools. You need AI that understands your business.

You need the semantic layer. The Domo semantic layer focuses on three key elements, the data models that define the relationships between the tables, the formulas that define the standard metrics your business uses and monitors, and the definitions of the metadata that give your rows and columns context. With data models, data owners define relationships between disparate tables once, and business users can explore the data without worrying about joins or rebuilding data sets. That means faster time to insight, consistent analysis, and the flexibility to evolve your data without recreating pipelines every time something changes.

Let me show you an example. Anyone who has connected data from a CRM knows you'll have lots of related tables. Now, after tidying up and ensuring the data quality, you can take those tables and define their relationships here in the data model. Each relationship includes the key joins and how the data is related.

Now, over in Analyzer, I can choose that data model just like I would any other data set. All of its columns, grouped by table, are available to use in a single visualization. This means you can do new types of analysis that traverse tables, like ordering accounts by revenue, but breaking out the revenue by product, or quickly showing revenue generated by sales account owner in a year without needing to change data sets or join them together in a new view. Data models and their relationship context will be available in AI Chat, so you can answer a wider variety of questions from a single source.

And as I mentioned earlier, Domo is a member of the Open Semantic Interchange, or OSI, helping to shape the standards that will move the entire industry forward. Eventually, this means that data models defined in the OSI standard in your data cloud will work natively in Domo. Next, have you ever been deep in your data, needed to make a quick change, and had to stop everything just to export it to Excel and re-upload it back into Domo? That friction slows down business.

That's why I'm excited to announce Worksheets is now generally available to all customers. With Worksheets, users can securely update, explore, and analyze data directly in Domo with the simplicity of a spreadsheet. No app development required. Now, let's take a look at how it works.

Picture this. As an inventory analyst, you quickly dive into your stock data right inside Domo. No exporting needed, just instant exploration. You can filter your data by region or warehouse, group records by product categories, and even add custom calculations on the fly to flag low stock items.

With features like in-chart building, conditional formatting, and column filtering, you can turn a massive data set into something actionable within minutes. You can create link tables to manage user-entered data, build charts that update in real time, and thanks to our cloud integrations, you can work directly with massive data sets in your CDW. Worksheets bridge the gap between curiosity and creation, making data exploration faster, simpler, and more accessible for business users. And if this becomes more than a one-time analysis, no problem.

With Worksheets, you can transition all of your work into App Studio to create a polished app for long-term use and distribution. And today, we're excited to announce our new inline chart editor is now generally available. You can make visualizations changes directly within the workspace without leaving your flow. No more jumping between Analyzer and App Studio.

Just a faster, more intuitive experience that empowers anyone to build production-ready apps tailored to their business. Next, I'm excited to announce one of our most requested features ever, PDF format support for Report Builder. Because no matter how interactive your apps are, executives still want that polished report delivered to their inbox at 6:00 a.m. on a Monday morning. Last Domopalooza, we previewed this vision, and now it's here.

Let's take a look. You start by dragging your visualizations right onto the canvas. It feels familiar, but the level of control you have here is entirely new. You can fully customize the layout to match your needs, from adding logos and branding to stamping confidential in the footer.

It's designed to ensure every report looks polished, professional, and aligned to your corporate identity. Now, look at this table. We all know the frustration of exporting a PDF and losing rows to bad formatting. With Report Builder, that problem disappears.

Pages automatically expand for large tables, headers stay sticky across pages, and reports remain clean, readable, and complete, with no missing data. You can also style the entire document to match your brand colors and themes instantly. Data should look great, and this tool ensures it does. The real power shows up when you share it.

You can build the report once, but every recipient gets a personalized version automatically. Programmatic filtering, PDP, and governance rules are all applied behind the scenes, ensuring each person only sees the data that they're authorized, enabling secure, automated distribution at scale. Now, for those that know me, you know I enjoy geeking out with data. Yes, it's true.

Working with data is one of my happy places. There's nothing more exciting than watching what happens when the right data lands in the right hands for the right purpose. And it's been amazing to see what our customers have done on top of your foundational data investments made in Snowflake, Databricks, BigQuery, and more. More customers than ever are leveraging cloud integrations in Domo to maximize their investments in existing infrastructure.

In fact, usage has grown 80% year over year, with more than 40 million monthly queries now flowing through the platform. And when we start to take a look at the next evolution of connectors, you use those connectors to bring data from different systems into a single place. The data itself is only part of the story. Understanding where that data comes from and what it means is valuable context.

And if we want to use that existing metadata instead of rebuilding it manually, I'm excited to announce that our top connectors are now AI-ready. We've added more column-level context to your data right from the start. We've done this by automatically populating your data dictionary, where you can tweak it as needed, so you spend less time documenting data and more time using it What about the data sources without an out-of-the-box connector? That used to mean workarounds or custom scripts, but we're expanding what it means to connect with a new AI-guided experience.

I'm thrilled to announce our AI assistant for the JSON No-Code connector, coming soon. Like many of you, I've pasted API docs into Claude more times than I care to admit, just to figure out what to do next. Now I can take advantage of that AI-assisted no-code experience right inside Domo. You tell the AI assistant what you want to connect to, and then AI takes over, handling the JSON settings and guiding you with plain language steps.

And because it handles 80% of REST API scenarios, you'll be able to bring in more systems with less effort. Now, even non-developers can connect APIs to Domo in minutes. One of the most powerful capabilities enabling AI inside Domo is Domo Documents, formerly known as File Sets. This allows organizations to securely bring unstructured content like PDFs, research reports, contracts, presentations, and policy documents directly into the Domo platform and make them AI-searchable using natural language.

Combined with your structured enterprise data, Domo can now provide richer context, more intelligent answers, and power AI agents that reason across both documents and live operational data in a fully governed environment. Support tickets, catalog descriptions, chat logs, images, PDFs, and long documents full of insights in free-form text. With Domo Documents, you can securely store your unstructured data files in Domo. All that unstructured data is also searchable and available for powerful use cases.

Now, your AI agents can use individual files as context or create a knowledge base by turning a document collection into a vector database to do RAG. Oh, and one more thing. You can bring those files into Magic ETL and extract information from them using the new Documents tile, turning unstructured data into structured data sets. The data nerd in me gets excited about what this unlocks.

Speaking of Magic ETL, Magic ETL powers so much of the important work you do every day, and we've taken your feedback to heart. Today, I'm excited to share updates that make Magic even more powerful and intuitive, helping users of all skill levels stay in the flow, debug faster, and better observe their data pipelines. Let's take a look. My favorite thing about Magic ETL is seeing our customers finally get their hands on their own data.

We love Magic ETL because it's a core part of how we deliver trusted analytics across the entire business, getting us from source to true impact faster. What I love about Magic ETL is that it lets people of all backgrounds collaborate on data transformation without needing to know SQL. You don't need to know complex code to do some really cool, powerful, impactful things. Use Magic ETL as the bridge to pull it all together.

It's right where your data is, it's right where your users are, and it just makes for this very intuitive, very simple, collaborative experience. The new anti-join feature has become very efficient and clean, especially if you're working with reconciliation data. The AI text generation tile tagged our data sets and allowed us to power a custom data set finder app that makes sure our content creators get with the ground running. Magic ETL, throughout the years, has really taught me how to think about data and about data transformation.

I think I've used it every day since. Thanks. Love hearing about those customer stories. The AI text generation tile has been our most highly adopted AI beta to date.

This tile gives you the effortless way to leverage generative AI, turning qualitative chaos into quantifiable insights. And I'm happy to announce it's on its way to GA. Input to Magic via the documents input tile, you can use the AI text generation to extract that data from your documents, giving you access to information you had previously had to retrieve by hand. Additionally, coming soon are two new Magic ETL tiles, classification and sentiment, designed to make AI-driven insights even easier to use.

They are some of the most common and valuable AI use cases we see today, and these new tiles simplify the experience so users of any skill can quickly unlock meaningful insights from their data. The new authoring experience features a fresh canvas interface designed to maximize what's important to you and minimize what's not. And with the new build-in-place capability, one of those unimportant things might very well be the action selection pane. So if dragging and dropping tiles make you twitch, just don't do it anymore.

Right-click anywhere on the canvas, including on the line connecting two tiles, to add a new action at that spot. With customizable panel layouts that follow you from data flow to data flow, user-level settings that persist between sessions, and yes, dark mode. This new canvas experience is all about helping you stay in that flow state, building in the way that feels most natural to you. Last year, we shared that we were delivering many of your top ideas from the Idea Exchange request, and we've continued that tradition.

First up, disable tiles. If you ever wanted to remove a tile temporarily without deleting it, as many of you requested, you can now simply disable tiles and keep your workflows intact temporarily, saving the tiles in a workflow, making it easier to debug, troubleshoot, or keep older logic around like that tattered little tile security blankets just in case that formula your colleague wrote in 2019 suddenly becomes relevant again. Next, the much-requested Run to Here is finally here, allowing you to preview only the section of a data flow you need. That means faster troubleshooting, quicker iteration, and far less waiting around.

And finally, row count observability. When you run a preview, you will now see row counts flowing out of every tile, making it much easier to spot issues like broken filters or exploding joins before they impact production reports. Your feedback continues shaping the product, so please keep it coming, and together, let's continue making Magic even better. Next up for the Domo admins who play a critical role in the organization, which is why we focus heavily on making administration simpler and more powerful.

From workspaces and enhanced navigation to pre-configured experiences tailored for different teams, we're helping admins create more consistent and governed user experiences. Let's take a deeper look at what these capabilities do. Workspaces, currently in beta, allows you to bring together the most important Domo objects, pin key items, and organize content into folders all in one place. And with navigation, individual users can personalize their experience in Domo by adding frequently used tools, dashboards, or apps to their personal menu for instant access.

Today, in addition to individual user personalizations of navigation, I am pleased to announce nav configs, now available in your instance. This allows admins to create consistent navigation experiences for everyone or for specific groups. This empowers teams with faster access to the tools, apps, and the data that matter most to them. How many of you are using Domo App Studio and/or App Catalyst to build rich user experiences?

Well, now you can take those apps on the go with native app distribution coming soon. With native app distribution, you can take that perfect experience you've curated and extend it to a wider audience, even those who don't have direct access to Domo. Your Domo apps can be deployed as standalone native applications in the iOS or Google Play stores. This means your users can now access exactly what they need, when they need it, all within the app that's branded for your company or group.

And what if you want to send a highly tailored app experience to a busy executive on the go? No problem. Instead of giving them your entire Domo instance, you give them a native app that is personalized and has exactly what they need, nothing more. Now it's time to talk about PDP.

As admins, you know how critical it is to control how users access and interact with data, and how difficult that can become at scale. That's why we're focused on delivering reusable governance at your fingertips. And today, I'm excited to announce global PDP policies. Global PDP policies are your one-stop solution for creating a policy once and reusing it everywhere in your data.

Become the ultimate admin and standardize your governance. Scale your PDP implementation by defining policies once and applying them across multiple data sets. With global PDP schemas and personas, you can simplify governance, reduce policy complexity, and still deliver the right data securely to every user. And already generally available, column PDP allows you to selectively redact or obscure sensitive column values for specific users or groups.

For example, HR may need access to employee salary data, while everyone else is restricted from seeing it. With column PDP, you can protect sensitive employee data while still allowing the broader organization to use that same data set. Instead of creating multiple data sets or workarounds, data can now be masked dynamically based on PDP policies. And before we wrap up the last of the product updates, we'd like to sneak one last thing in.

Yes, you've been asking for it. It was the most upvoted ideas exchange request, and it's finally in progress. Introducing user impersonations. It's the ultimate admin tool, allowing you to see Domo exactly as your users do, troubleshoot issues faster, and deliver a better support experience.

Governance remains built in with controlled access and audit rationale for every impersonation request. Instead of lengthy troubleshooting calls, admins can quickly step into a user's experience and resolve issues directly. So we hope these capabilities leave you feeling even more empowered as Domo admins and users. As we come toward the end of today's session, we've covered a huge amount of innovation, from AI agents and agent builder, to cloud data warehouse integration, data models, Magic ETL, worksheets, governance, and enterprise-grade security.

But let's come full circle back to where we started. AI is only as good as the foundation beneath it. Trusted governed, connected data is a critical foundation for every successful AI strategy, and that's a big part of why you're already using Domo today. The exciting opportunity now is how you leverage that foundation to accelerate the next phase of your journey toward becoming a truly intelligent enterprise.

Through your partnership with Domo, you're not starting at step one. You already have a strong AI-ready foundation. Domo is built for this moment because every AI initiative depends on trusted governed, connected data with the right access controls in place. And where AI starts delivering real business value is through purpose-built tools, data-powered apps, automations, and increasingly agentic workflows that can reason, act, and solve problems using context and business knowledge.

A lot of companies working to adopt AI across their organizations to solve problems, and it's working occasionally, but there's a better way. There's a path to really drive value and take AI towards unlocking value for organizations. Simon Sinek coined the term "Start with why." This book emphasizes that best organizations are the ones that understand why they exist. This hasn't changed and is now more important than ever.

If you lack clarity around what matters to you, how do you convey that to an AI tool? And if you can't, you get hallucinations and drift and end up in endless POCs and experiments. The why is critical, but let's also talk about the people. Change is uncomfortable, and AI can feel disruptive, but the reality is the world is changing.

The opportunity is to remove the busy work nobody enjoys doing and allow people to focus on more meaningful, valuable work. One colleague of mine calls this the anti to-do list. AI shouldn't be viewed as a threat, but as a way to drive efficiency and empower people, because ultimately, people are what make AI successful inside an organization. So we've talked about the why, the people, and gaining efficiency.

The next step is understanding your processes, mapping them clearly, and identifying the tasks no one enjoys doing and where AI can create the quickest wins. You don't need AI to replace everything on day one. The most successful AI journey starts small, solve one meaningful problem well, and expand over time. That's the opportunity, one step at a time.

Now, one of the biggest challenges organizations face with AI isn't the technology at all. It's knowing where to start, which use cases deliver value fastest, and how to operationalize AI securely and at scale. To help you on that journey, we built Domo AI Planner and made it available to our customers. The AI Planner helps identify high-impact opportunities, align AI initiatives to business outcomes, and create a practical roadmap for adoption, all leveraging the trusted foundation you already have in Domo.

Scan the QR code or visit the URL to get started, and while you do that, I'll walk through a quick demo of the app. So here we are on the webpage with the AI Planner app, and it's built in Domo and exposed as an app on the web. So we can start with some existing suggestions, or we can build a process from scratch with the process builder. So here, you can simply use natural language to query.

In this case, we want to build an AI campaign monitor that consistently and constantly monitors how we're progressing for marketing spend to get the best ROI. It will allow you to iterate and ultimately come up with a list of processes to identify which process, one or more of those processes, that can be created using agentic solutions. Once you have the processes mapped out, you can then take it to the next level to see what's happening, the different steps, as well as a solution architecture. From here, I can copy a prompt, and I can quickly paste that into App Catalyst, which we saw a few moments ago, and start to iterate and prototype on what this app could look like.

So in a matter of minutes, I can go from process ideation, identification, and a prototype of how this may look visually, and then I can publish it. That really short-circuits the outcomes and brings quicker value to you as you go through this process. Also, we've got some great starting points for you. We've got templates for you, and I would encourage you to check these out.

We've captured a number of agent templates from our customers and partners, part of the amazing things the Domo ecosystem is doing with AI on the Domo platform, and those are here. Please go ahead and check those out. As we wrap up today, hopefully what you've seen is that AI is no longer something reserved for the future. It's here right now.

And the organizations that succeed will be the ones that combine trusted data, intelligent automation, and empowered people to drive faster and smarter decisions. Domo is uniquely positioned to help you on that journey because you already have the critical foundation in place. Now, the opportunity is to build on that foundation and identify the AI use cases that can create real impact across your business. And we would love to partner with you to explore those opportunities together.

So please reach out to your account team and schedule a working session, and we will help you accelerate your journey toward becoming a truly intelligent enterprise. Thank you, and I hope this session was useful for you.

‍