Governed Data for Agentic AI

Join Domo’s CMO, Mark Boothe, and Jeff Clobes, Solution Engineer, Domo, as they pull back the curtain on a bespoke pro-code application that solves a tough challenge in every Domo rollout—getting people to log in the first time and keep coming back—by borrowing the mechanic that already runs every office fantasy league. Jeff will walk through how the app clones the personalities of four opinionated pundits, pits users against an algorithmic rival manager, generates hot takes and a full weekly audio recap grounded in real MLB game data, and writes every submitted pick and scored day back to a governed Domo AppDB collection the moment a user locks it in. All of this is engineered end to end on Domo.

What You Will See:

• It's Agentic: The app doesn't just visualize data; it analyzes daily performance, generates in-character takes from four distinct pundits, produces a Hot Take of the Day chyron, drafts a rival manager's deadpan reaction, and delivers a fully-scripted 2–3 minute audio broadcast with mood-detected intro music tuned to the week's outcome.

• It's Connected: One application, every layer. A custom pro-code front end, live queries against a governed Domo dataset, Domo AI calling foundation models for every take and recap, AppDB for pick persistence and scored daily reports, and browser-native voice synthesis giving each character their own sound—natively integrated, reading where it should and writing where it matters.

• It's Habit-Forming: Fantasy sports mechanics engineered into the fabric of Domo. Standings, roasts, weekly recaps, streaks. There’s no corporate onboarding, compliance training, or forced adoption. Just something people already want to check.

AI can spin up a slick prototype in seconds, but a demo that looks ready and a system that actually ships and gets adopted are two very different things. In this episode of Domo’s podcast, Governed Data for Agentic AI, Chris Willis, Chief Design Officer at Domo, speaks with Dan Hendriksen, who leads Domo’s Advanced Customer Enablement (ACE) program and spends his days helping customers turn AI experiments into things they can actually run. He’s watched the same patterns play out across build after build, and he’s here to share what separates the projects that ship from the ones that stall.

This conversation is all about “plausibility theater”: the trap of building something that looks like it should work but quietly skips everything real systems need (user volume, concurrency, security, edge cases). Dan explains why the planning conversation matters more than ever now that AI has taken the developer out of the loop, why “do not code” and plan mode are becoming essential habits, and why the time you save on a prototype is best spent up front with stakeholders instead of iterating 45 times on the wrong thing.

Chris and Dan also get into the bigger shifts AI is setting off: the rise of curious generalists over stay-in-your-lane specialists, the long tail of low-value problems that’s finally worth solving, and the move toward bespoke apps that do exactly what a team needs. Along the way Dan makes the case that some of the best AI is maybe not AI at all, and that it all starts with a deceptively simple question: Why? Listen for a practical, field-tested take on getting past the demo and building AI that ships and works.

After listening, you'll learn:

• What “plausibility theater” is and how to avoid it

• Why the planning conversation beats jumping straight to code

• How roles are shifting toward curious generalists

• When the right answer is a simple automation, not an app

Join Domo CMO Mark Boothe and Ron Karas, Principal Solution Engineer at Domo, as they pull back the curtain on a repeatable, AI-driven approach to operational data migration, built for organizations where the next acquisition is already on the calendar. Ron will walk through why these projects are so costly, then prove the alternative end to end on Domo: taking a real Microsoft Dynamics 365 Business Central customer extract, using genuine Microsoft-documented field names, and having the Domo plugin automatically generate, run, and verify a working ETL that outputs SAP-ready data. The use case is ERP, but the pattern travels, CRM, financial systems, and proprietary systems all migrate the same way. And you can get this live in hours with no new tooling on the Domo platform.

In this episode, CMO Mark Boothe sits down with Zach Ehasz, Director of Product Management for Hospital Quality at Healthgrades, to unpack how his team turned a decades-old sales tool into an AI-powered discovery engine. AMT had become a 100MB+ macro-enabled Excel workbook that broke constantly and spat out five static reports. Rebuilt on Domo with AI agents and the Context Engine, it now surfaces unique, comparative award messaging across city, state, and national levels in minutes instead of days. A masterclass in putting AI to work on your own data, safely.

Miles Herleikson presents an AI Command Center for franchise developers managing 50 to over 500 locations. This system monitors deal velocity, analyzes market expansion opportunities, detects store opening risks, forecasts revenue impact, and benchmarks franchisee performance—all in a single view.

Ben McClave of Yum! Brands shares his AI-first approach to business intelligence, from an app that builds apps to vibe-coded dashboards wired to a Snowflake Semantic Layer. This is a candid look at moving fast without breaking trust.

Scott Pulley shares a retrieval-augmented generation app built with Domo Documents as the backbone. This Intelligent Response Engine drafts RFPs using your institutional knowledge, security documentation, knowledge base, and past RFPs.

Every recruiting team has a backlog. Open reqs aging past SLA, hot jobs buried in spreadsheets, and recruiters spending their best hours building the briefs that should already be in front of them. What if your data could do that work instead?

At Domo, we built an AI Recruiting Agent that doesn't just surface the problem. Instead, it tells you what to do about it. The agent reads your Workday data, scores every open requisition for time-to-fill risk, segments your pipeline into Critical, At-Risk, and Healthy, and generates a recommended next action for each one—with the rationale built in. When a recruiter agrees, one click routes the decision through a governed workflow, logs it to AppDB, and sends a confirmation. Your best strategic thinking, automated. Your team's judgment, preserved.

Join Domo CMO Mark Boothe and Kenny Scott, Solution Engineer at Domo, as they walk through a live build of the Domo AI Recruiting Agent end to end, on the Domo platform. You'll see how App Studio, Workflows, Code Engine, and Domo AI work together as a single connected system; the agent analyzes your pipeline in real time, generates recommendations your recruiters would have spent hours writing, and routes every decision through a human before anything moves. There's no autonomous action and no black box. Just your data, your judgment, and AI doing the heavy lift.

Built around a national retail operation, the AI Business Investigator starts every morning by answering the questions leaders already care about: How did we perform yesterday? Which regions missed plan? Where is inventory at risk? Which promotions are working? Then it goes further. It evaluates signals across sales, traffic, conversion, inventory, marketing, fulfillment, and customer experience to identify material conditions and unexpected relationships that otherwise go unnoticed.

Company revenue may be above plan while one region is quietly deteriorating. Traffic may be increasing while conversion collapses. Marketing may be creating demand for inventory that stores no longer have. Instead of waiting for someone to notice the symptom and ask why, the investigator surfaces the condition, connects the evidence, explains what is happening, estimates the business impact, and recommends what to do next.

The goal isn't just to answer questions faster. It's to surface the signals and patterns you didn't know to look for, and to connect signals across the business that aren't obvious in any single dashboard.

Featured Session: Inside the AI Business Investigator

Join Domo CMO Mark Boothe and Dan Wentworth, solutions engineer manager at Domo, for a live look at an AI-powered retail decision engine built on Domo. We'll start where traditional analytics usually ends: a healthy executive brief showing revenue, traffic, conversion, inventory, and promotional performance. Then we'll launch the Investigator and ask a different question: What is happening in the business today that we haven't thought to look for?

You'll see the investigator detect a condition hidden beneath positive company-level performance: one region's revenue is falling even as customer traffic increases. From there, it connects signals across store performance, inventory, marketing, fulfillment, and customer feedback to uncover the underlying issue.

The investigator doesn't stop at the anomaly. It builds the evidence trail, estimates financial impact, recommends a cross-functional response, and routes the decision into a simulated Domo Workflow where a human can approve the next action.

Designed for retail, but applicable anywhere conditions change faster than people can monitor them.

WHAT YOU WILL SEE

• Answers before you ask: The daily brief automatically answers the questions retail leaders ask every morning.

• AI-detected conditions: The investigator looks for material changes and unexpected relationships not visible in standard reporting.

• Cross-functional investigation: AI connects sales, traffic, conversion, inventory, promotions, fulfillment, and customer feedback to explain the underlying issue.

• Evidence and impact: Every finding includes supporting metrics, confidence, business impact, and why it may have been easy to miss.

• From insight to action: Recommended responses can be routed into Domo Workflows for human approval and operational follow-through.

What if you could identify which employees are at risk of leaving before they start sending resumes?

Domo’s AI-native Employee Retention Intelligence Agent turns disconnected workforce data into a proactive retention system. It connects information from HRIS platforms, compensation history, engagement surveys, and performance reviews to score employee flight risk daily and explain the factors behind each signal.

When elevated risk is detected, the solution generates AI-assisted context and a recommended retention plan, then routes it to the appropriate manager or HR partner for review and action. Each intervention is logged, tracked, and measured to HR leaders can see whether managers are responding and which actions are improving retention.

The result is a more consistent, informed approach to employee retention – helping managers address concerns earlier and allowing HR teams to focus on the conversations and actions that keep valuable employees engaged.

Featured Session: Inside the Employee Retention Intelligence Agent

Join Brendan Carr, Solution Engineer at Domo, for a demonstration of how Domo can turn employee data into a proactive retention operating system for a fast-growing tech company.

The session will show how the agent:

• Unifies signals from HRIS, compensation, engagement, and performance systems

• Scores employees daily using explainable risk factors

• Generates personalized retention plans and manager talking points

• Routes escalations to HR with full context attached

• Tracks manager accountability from the initial signal through resolution

Built end to end on the Domo App Platform, the solution can be deployed in weeks without replacing existing HR systems. Personalized data permissions ensure managers see only their direct report, while HR maintains appropriate oversight.

Why It Matters

• It’s Agentic: The solution goes beyond dashboards by identifying risk, explaining contributing factors, recommending interventions, and routing actions to the right person with human approval at critical steps.
• It’s Connected: App Studio, Domo Workflows, Magic ETL, Python-based modeling, and existing HR data work together in one application.
• It’s Governed: Access is restricted by role, HR reviews escalations, and every retention action is logged and measured. There are no autonomous employment decisions and no unnecessary exposure of employee data.

See what happens when employee data stops being a report and becomes a governed, measurable retention system.