Systems | Development | Analytics | API | Testing

Introducing Arvix AI by Unravel Data An operator. Not an advisor. runarvix.ai About Unravel Data Agentic data platform optimization, powered by an AI engine that continuously optimizes performance, cost, and reliability across Databricks, Snowflake, and BigQuery.

Check out the repo here. Manually vetting hundreds of project requests is a thing of the past. Imagine receiving every proposal with a built in risk score, resource check, and "Go/No-Go" recommendation—delivered in seconds. Join Kevin Blanco as he demonstrates how to build a powerful multi-agent system that seamlessly integrates Google Cloud and Asana. Watch along and see a real world example of automating an infrastructure request, returning instant historical pattern analysis and live workspace context without any manual steps.

Snowflake Summit 2026 kicked off with an opening keynote on The Agentic Enterprise — featuring a conversation between Snowflake CEO Sridhar Ramaswamy and Anthropic Co-Founder and President Daniela Amodei on how AI agents are reshaping how enterprises work.

Ever wonder why so many enterprise AI projects never make it past the pilot stage? It’s not the AI—it’s the foundation. In this video, we break down why rushing into complex models without fixing inconsistent data, fragile pipelines, and afterthought governance is a recipe for failure. Fix the basics first!

Are you actually building an open data platform, or are you just using open source file formats inside a new type of vendor lock-in? Many organizations assume that migrating to Apache Iceberg or Parquet automatically makes their data architecture open. However, true architectural freedom requires a strategy that spans across your entire data estate—not just the storage layer.

Is your organization actually driving value with AI, or just scratching the surface? USC's Founder of the AI Trust Lab, Shub Agarwal, joins to share his definitive 9-step playbook to take AI from concept to production without burning your budget.

Shub Agarwal (Founder of the AI Trust Lab at USC) flips the script. Stop over-investing in massive data overhauls. Instead, reverse your approach: start with a brutal business problem, pull only the specific data needed to solve it, and build incrementally. Chief Data & AI Strategy Officer Cindi Howson agrees that true value comes from scaling immediate business impact, not waiting for a flawless architecture that will never arrive.