Beyond RAG: A Relational Context Engine That Cuts Token Burn — Unblocked

This post introduces a 'Relational Context Engine' as an advancement beyond traditional RAG. It addresses the limitations of vector search for answering structural questions about work (e.g., 'which PRs did I merge last week?'). The engine automatically discovers schemas, resolves identities across systems, validates queries to prevent dangerous operators, implements retries that feed errors back to the model, and integrates full-text search. This approach demonstrably reduces token burn (up to 50% in a demo) and improves agent accuracy by providing structured, contextual information. A simulator is also provided for testing the effectiveness of pre-gathered context.