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.

Companies are spending more on AI than ever and seeing almost none of it show up in the P&L. In this episode of Domo's podcast, Governed Data for Agentic AI, Mark Boothe, Chief Marketing Officer, sits down with Chris Willis, Chief Design Officer and AI Futurist, for an honest, hype-free read on where agentic AI actually stands.

They dig into the "J-curve" that explains why productivity gets worse before it gets better (the same dip that hit the PC), why handing teams more tools stalls progress when mindset and enablement should come first, and why most AI usage is invisible to the leaders who assume they can see it.

Chris lays out his VPC model (visibility, predictability, and control) as the practical path from cool pilot to something you can trust in production, while Mark shares hard-won lessons from transforming his own marketing org, including the Domopalooza keynote videos his team produced for $1,700 instead of hundreds of thousands. Listen for a clear-eyed take on crossing the productivity dip, closing the governance gap most companies are ignoring, and building agentic AI that (dare we say) actually pays off.

After listening, you'll learn:

• The productivity J-curve, and why a slow payoff is normal
• The mindset-before-tools AI operating model
• Chris Willis's VPC model for trustworthy agents
• Why governed data is Domo's foundation for the agentic era

Tyler Clark, Solutions Engineer Manager at Domo, walks through a custom pro-code app built for a community bank tackling siloed reporting, regulatory complexity, and proactive loan portfolio management. It unifies bank-wide KPIs into one executive command center, uses Snowflake Cortex AI to model rate scenarios and flag NIM compression risk early, centralizes AML alerts, SAR filings, and KYC deadlines in a governed compliance center, and surfaces early warning signals so credit officers can act on deteriorating loans before migration.

The legal industry is entering a new era, and Domo AI is helping lead the transformation. AI is no longer just a buzzword—it's becoming an everyday tool for litigation teams.
Join us as we demonstrate how Domo AI streamlines legal workflows by identifying expert witnesses, generating medical chronologies, drafting demand letters, etc.

Are you ready to turn every coach in your organization into your sharpest player development strategist? Watch us demo a live, pro-code Baseball Intelligence Platform that analyzes game logs and swing mechanics to surface player development flags and pitcher workload risks. We'll walk through how the platform generates full 90-minute practice plans grounded in real data and routes personalized take-home drills directly to a family portal—all with human-in-the-loop coach approval. This is what happens when every practice plan, pitcher decision, and family touchpoint runs on agentic AI built entirely on the Domo App Platform.

Domo unifies real-time operational data into AI-ready data products, enabling AI agents and human decision-makers to optimize routing, reduce boil-off gas losses, minimize fuel and demurrage costs, and improve fleet utilization—unlocking potential savings of $600K–$1.2M per LNG voyage.

In this livestream, marketers, analysts, and team leaders learn a practical path. Start small with one agent, then use Domo's MCP to activate AI on governed data. Examples shared include a paid-media insights agent and creative work produced in less time, drawn from a shared knowledge base and delivered where teams already work.

Most companies get Snowflake right and stop there. Domo's Mark Boothe and Chris Hunter show what happens next. A Revenue Command Center federates governed data via Cloud Amplifier without copying it, while Cortex Analyst and Cortex agents answer and act with RBAC and full audit trails. Every AI-recommended retention plan still gets a human-in-the-loop approval before it runs. This is agentic AI built on Snowflake, extended to your whole organization, not just your data team.