Systems | Development | Analytics | API | Testing

Customers and champions report problems in Slack, but if nobody files the ticket, the issue disappears before it ever reaches Jira. In this video, we use AgentSpot to build a Slack to Jira Coverage Workflow that reads your champions channel every morning, cross-compares it against your Jira backlog, and emails you a report of every issue raised in Slack that no one has filed yet. What is AgentSpot? AgentSpot is an Agentic Workforce Platform for building workflows that make decisions, take action, and deliver results across every system your business runs on, grounded in your data.

Discover what’s possible with AgentSpot as Sheila showcases an AI agent ("Leasey") built to automate lease accounting. From analyzing contracts to creating calculations, schedules, and audit documentation, this workflow shows how teams can use agents to streamline everyday business processes. What is AgentSpot? AgentSpot is an Agentic Workforce Platform for building workflows that make decisions, take action, and deliver results across every system your business runs on, grounded in your data.

Check out what’s new in ThoughtSpot’s latest release! Spotter User-Level Personalization: Spotter now builds memory from your individual conversations, remembering your personal preferences, so it adapts to how you work and you spend less time repeating yourself. SpotterViz for Embedded Liveboards: Embed SpotterViz directly into your embedded smart dashboards and empower your users to build, edit, and explore decision-ready dashboards in minutes.

For most enterprises, autonomous AI agents still feel like a risk waiting to happen. Andi Gutmans, Vice President and General Manager for Data Cloud at Google, joins Cindi Howson to explain what it takes to build the data foundation that trustworthy agentic AI depends on. He breaks down how organizations can finally activate the 90 percent of enterprise data that's unstructured, why tokenmaxxing is the wrong way to measure AI value, and how open standards like Apache Iceberg are helping leaders tear down fragmented, multi-cloud data silos and unify data across clouds.

Silicon Valley has been measuring AI success by token consumption. The more tokens, the more AI transformation. Right? Wrong. Andi Gutmans, Vice President and General Manager for Data Cloud at Google, joins Cindi Howson on the podcast to share that the best context is the context that drives the outcomes you need with the least amount of tokens and processing. Efficiency, not volume, is where the real value is.