Audi & Storm Reply: GenAI multi-agent devbot for cloud security, cost optimization, and IaC on Amazon Bedrock
AUDI AG, in partnership with Storm Reply, built a production-ready generative AI devbot for its Cloud Foundation Services team. The solution supports internal cloud management by helping with security findings remediation, cost optimization analysis, validated infrastructure-as-code building block retrieval, and AWS architecture guidance. It uses a serverless multi-agent architecture with Amazon Bedrock, Bedrock Knowledge Bases, Bedrock Guardrails, AWS Security Hub, AWS Cost Explorer, Amazon OpenSearch Service, AWS Lambda, Amazon S3, and AWS Well-Architected guidance.
- Organization
- Audi
- Industry
- Automotive
- Location
- Germany
- Published
- May 2025
Reported outcomes
−99%
Well-Architected documentation lookup time reductionTime & speed
Strategic outcomes
Catalog median for time & speed deployments: −60% across 724 reported metrics. Compare benchmarks →
Primary read
Use case focus
Showing 3 of 4
- 1Agentic AI
- 2Internal Developer Productivity
- 3Cloud Operations
- Manual cloud security, cost optimization, IaC retrieval, and architecture guidance work was slow and error-prone.
- Audi needed a robust, scalable, low-latency solution that could integrate with existing systems and comply with internal security and policy requirements.
- Built a production-ready serverless multi-agent architecture with specialized agents for Security Findings, Cost Optimization, validated IaC Building Blocks, and architecture guidance.
- Used Amazon Bedrock Knowledge Bases with Amazon OpenSearch Service vector search for RAG-grounded responses, Amazon Bedrock Guardrails for policy compliance, and AWS Lambda-based orchestration to route requests to the right agent.
- Integrated AWS Security Hub and AWS Cost Explorer as data sources, stored validated code blocks and conversational memory in Amazon S3 and OpenSearch, and added multilingual support plus reranking for retrieval quality.
- The solution reduced Well-Architected documentation lookup time by nearly 99%.
- Manual IaC building block retrieval that took around 10 minutes was reduced substantially.
- Security findings remediation time and cost-report generation time were reduced.
- Audi reported up to 76 minutes per day saved across a typical mix of tasks.
- The solution also reduced errors and improved reuse, deployment speed, and user productivity.
Architecture
A production-ready serverless multi-agent architecture routes user requests through a custom AWS Lambda orchestrator to specialized agents. Security and cost agents query AWS Security Hub and AWS Cost Explorer. The architecture agent uses Amazon Bedrock Knowledge Bases with an Amazon S3 source adapter and Amazon OpenSearch Service vector store for retrieval-augmented generation grounded in AWS documentation. The solution includes Amazon Bedrock Guardrails, multilingual streaming responses, conversational memory in OpenSearch, validated IaC retrieval, and scalable modular agent expansion.
Implementation partners1
Sources & evidence1
The same organization appears in newer AI deployment evidence.
- Same organization re-documented as recently as 2026.
Measures whether this deployment's public evidence persists — not whether the system is still in production.
AI-generated summary. Verify important details with the linked sources before relying on this case.
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