Systems | Development | Analytics | API | Testing

[Finance Demo] AgentSpot Use Case - Procurement Automation: PR Approvals & Virtual Card Management

The procurement team at ThoughtSpot built two AgentSpot agents to tackle manual, time-consuming workflows — and the results speak for themselves. Agent 1 – Coupa PR Approval Nudger: Automated purchase requisition reminders that once took hours of manual chasing in Coupa and Slack. Approval cycle time dropped from 6.62 days to 2.8 days. Agent 2 – Virtual Card Intelligence: Cross-validates PO and requisition data against Spend Flow to surface budget leakage, flag expiring cards, and send personalized Slack outreach to card owners. All without manual audits.

[Finance Demo] - AgentSpot Use Case - Virtual Card Spend Oversight

Manually cross-validating virtual card data across disconnected systems was a constant pain, until the procurement team built an AgentSpot agent to do it automatically. This video showcases a Virtual Card Intelligence agent that pulls PO and requisition data from Google Drive, cross-validates it against Spend Flow, flags expiring cards and utilization risks across 30/60/90 day bands, and sends personalized Slack outreach to card owners. Plus a full 9-tab Excel report covering KPIs, expiry, utilization, and reconciliation. The best part? This is all done in just 4-5 minutes.

Snow Report: What's Happening At Snowflake in September

The September Snow Report is LIVE Three GA launches, AI cost controls, and Expedition 2026 registration is open. What's new Per-User Quotas are GA Set daily or monthly spending limits per user for CoCo, CoWork, Cortex AI Functions, or warehouse compute — and Snowflake blocks access automatically when limits are hit. Deep Research in Snowflake CoWork is GA Multiple agents analyze your structured data, unstructured content, and external context together and deliver a fully cited report with recommendations in minutes.

SpotterCode in the Visual Embed Playground: Faster Embedding, No Setup Hassle

Embedding ThoughtSpot into your application just got dramatically faster. SpotterCode is now in the Visual Embed Playground. Ask in plain language (rename an agent, apply a custom theme, configure an embed component), and SpotterCode generates exactly the code you need, right inside the ThoughtSpot app. In this video, see how SpotterCode eliminates the setup friction that slows down every embedded analytics build and what it looks like to go from question to working code in seconds.

Simplify Data Integration | Do It Better with Infometry & Snowflake"

Discover how Informometry’s Snowflake-native applications streamline data integration, governance, and analytics. With no-code connectivity, replicate enterprise data from platforms like Netsuite and Salesforce directly into Snowflake. Eliminate complex ETL processes and reduce integration costs while keeping data secure.

Why Your AI Strategy Needs Both Shared and Shared-Nothing Storage

As enterprises scale AI initiatives from the core data center to the edge, many organizations are thwarted by weak data practices and fragmented systems. The attempt to use a one-size-fits-all architectural approach for workloads that have fundamentally different needs is no longer a solution. If your AI ambitions are outgrowing your storage: the solution isn’t just adding more capacity, but matching the right architecture to the right stage of the AI lifecycle.

Qlik Script Editor Gets a Major Upgrade

Qlik Cloud just introduced a modern, IDE-grade editing experience for the Data Load Editor and Script Editor — now available in Public Preview. In this video, Michael Tarallo walks through what's new, including dark mode, improved syntax highlighting, code folding, smarter navigation, autocomplete, and code refactoring with Rename Symbol. Learn how to activate the Next-Gen Script Editor in your tenant and see how these updates make everyday Qlik scripting faster and more intuitive.

What's Next Is Not More AI. It's Better Foundations.

The next real advantage in artificial intelligence will not come from the next AI tool or application. It will come from a stronger data foundation beneath it. At Hitachi Vantara we work every day with customers on the data supporting their systems. That vantage point has led me to a simple conclusion: the leaders who pull ahead will not be the ones with the most advanced AI. The leaders will be those whose data foundations are strong enough so that AI can be trusted to act.