The Challenge
One of the world's most respected automotive manufacturers faced a critical knowledge bottleneck: engineering project data was fragmented across multiple platforms, making data lineage tracking, aggregation analysis, and document retrieval slow and error-prone.
The Solution
We designed and delivered a multi-agent AI framework built on AWS Bedrock, combining three specialised agent types: Knowledge Graph Agents for relationship mapping, Text-to-SQL Agents for structured data querying, and RAG-based retrieval agents for semantic document search. The system was integrated with Informatica for data management and deployed on a robust AWS cloud infrastructure.
The Impact
Engineering teams can now query project management deliverables in plain language, instantly retrieve relevant documentation, and trace data lineage across the organisation. Information that previously required cross-platform manual searches is now a single conversational query away.
Reflection Question: How much engineering time is lost each week to manual data retrieval across fragmented platforms? What decisions could be made faster if your data was always one question away?
Interested in an agentic AI framework for your engineering organisation? Let's explore what's possible.