Sanofi builds Concierge, an agentic generative AI assistant on Amazon Bedrock
Sanofi built Concierge in-house on AWS as a unified, agentic AI companion for its global workforce, using Amazon Bedrock for model flexibility and planning to add Amazon Bedrock AgentCore for orchestration. The system gives employees a single conversational interface for finding information, generating content, completing tasks, and discovering specialized agents across the company.
Reported outcomes
−92%
timeTime & speed
Strategic outcomes
Catalog median for time & speed deployments: −60% across 724 reported metrics. Compare benchmarks →
Primary read
Use case focus
Showing 3 of 3
- 1AI agents
- 2Employee productivity
- 3Workflow automation
- Scale an internal AI companion across a global pharmaceutical workforce while preserving flexibility and strong data sensitivity controls.
- Move beyond basic summarization as employee requests became more complex and the tool became a primary digital gateway.
- Built Concierge in-house on AWS using Amazon Bedrock and a model-agnostic architecture.
- Deployed across multiple regions to reduce latency.
- Added an agent hub/orchestration layer connecting the companion to specialized agents for data retrieval, system write-back, and workflow automation.
- Reached 50,000 weekly users and 72,000 monthly users.
- Generated 11 million conversations and 90% positive feedback.
- Surveyed employees reported 90.5% time savings on routine tasks, 78% better decisions, 77% improved work-work balance, and one use case cut verification time by 92%.
Architecture
Sanofi built Concierge in-house on AWS as a model-agnostic AI companion using Amazon Bedrock. The architecture was deployed across multiple regions for lower latency and expanded into an agent hub/orchestration layer that connects the assistant to specialized agents for data retrieval, system write-back, and workflow automation. Sanofi plans to incorporate Amazon Bedrock AgentCore to build, connect, and optimize agents securely at scale.
Sources & evidence1
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