Hyundai AutoEver: Building a multi-tenant generative AI sandbox and production AIOps on Amazon Bedrock

This article describes how Hyundai AutoEver built a secure, multi-tenant GenAI Sandbox on AWS that accelerates generative AI development across the organization, along with two production-grade multi-agent AIOps systems deployed on it.

• GenAI Sandbox uses single-account multi-tenancy with ABAC tagging for isolation, inherited security controls, and automated cost governance
• ErrorWatcher: sequential LangGraph pipeline with four specialized agents (Monitor, Detective, Solver, Reporter) reduced MTTR from hours to 5 minutes
• Big data incident response agent: 14-node parallel LangGraph workflow with delta-based state merging, self-falsifying RCA, and human-in-the-loop approval
• RAG with per-agent metadata filtering reduces token costs; aggregation-first log triage avoids expensive model calls
• Parallel reasoning with independent RCA models and a Reflector mitigates confirmation bias through self-falsification
• Operational safety enforced through read-only diagnostics, checkpointed workflows, and human approval gates

The patterns—ABAC multi-tenancy, typed LangGraph state with reducers, filtered RAG, and adjudicated parallel reasoning—provide reusable building blocks for enterprise AI adoption on Amazon Bedrock and OpenSearch.