Session
AstraZeneca's Multi-Agent System: Lessons Scaling Agents by 10x With Agent Bricks
Overview
| Experience | In Person |
|---|---|
| Track | Artificial Intelligence & Agents |
| Industry | Healthcare & Life Sciences |
| Technologies | AI/BI, Databricks SQL, Agent Bricks |
| Skill Level | Intermediate |
AstraZeneca built a multi-agent system using Agent Bricks to transform how commercial teams access pharmaceutical data. The Brand Assistant uses a supervisor agent coordinating specialized sub-agents across therapeutic areas, combining structured data via Genie Spaces with unstructured documents via Knowledge Assistant.
Unity Catalog integration with Entra ID enforces strict permission boundaries. MCP unlocks third-party tool integration.The architecture scaled from 5-agent POC to 20+ agents in production, designed for 50+.
Key components:
- Multi-Agent Supervisor for orchestration
- Genie Spaces for NL-to-SQL
- Knowledge Assistant for documents
- Unity Catalog for row/column-level security
- MLflow for tracing.
This session covers:
- Multi-agent architecture patterns
- Permission-preserving design
- When to split supervisors vs. add agents
- Human-in-the-loop testing
- Why bad data breaks agents regardless of tech
- Organizational challenges of agent ownership
- Lessons from scaling
Session Speakers
Brian Burke
/Senior Director, Platform Engineering
AstraZeneca
Homayoon Moradi
/Staff Data Scientist
Databricks GmbH