From Bowls to Bots: CAVA's Ask Astro Multi-Agent Supervisor on Databricks

At CAVA, we serve Mediterranean bowls to millions of guests — and data insights to hundreds of employees. But getting those insights used to take hours of analyst time and SQL knowledge. Not anymore.

Meet Ask Astro: CAVA's production multi-agent supervisor that lets anyone ask any data question in plain English and get accurate answers in seconds. "What was our top-performing restaurant yesterday?" "Show me loyalty redemption rates by region." "Find the Jira ticket about catering sales." Ask Astro routes each question to the right specialized agent — finance, operations, customer analytics, HR, Jira, or the web — then synthesizes a unified answer.

In this session, you'll see how we built it:

• Multi-agent orchestration: Why a supervisor pattern beats a single monolithic agent, and how we route questions across four Databricks Genie spaces, Atlassian APIs, and web search
• Production guardrails: How we prevent hallucinations, block sensitive queries (compensation, PII), enforce content safety, and handle edge cases at scale
• From prototype to production: The hard lessons from deploying in Databricks Apps and Slack — what broke, what we rebuilt, and how we earned trust with real users
• Measuring success: Adoption metrics, time savings, and ROI beyond the demo
• Live demo: Watch Ask Astro answer real CAVA business questions in real-time, routing across multiple agents and data sources

You'll leave with:

• A blueprint for building your own multi-agent supervisor
• Prompt engineering and routing strategies that work in production
• Guardrails and safety patterns for enterprise AI
• A roadmap from "cool prototype" to "thousands of daily users"

Whether you're building your first agent or scaling your tenth, this session will show you how to turn bowls of data into bots that actually ship. And yes, the bot will be there to explain itself.