Session

AstraZeneca's Multi-Agent System: Lessons Scaling Agents by 10x With Agent Bricks

Overview

ExperienceIn Person
TrackArtificial Intelligence & Agents
IndustryHealthcare & Life Sciences
TechnologiesAI/BI, Databricks SQL, Agent Bricks
Skill LevelIntermediate

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

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Brian Burke

/Senior Director, Platform Engineering
AstraZeneca

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Homayoon Moradi

/Staff Data Scientist
Databricks GmbH