Source Enrichment & Augmentation

Context

Your knowledge lives in systems of record — git history, Confluence, Jira — that speak their own formats, change continuously, and are noisy for a language model to read directly.

Consider these patterns first

Problem

How do you turn continuously-changing operational sources into clean, current, LLM-friendly material an AI can actually reason over?

Solution

Connect the sources and render them down at the point of use: Confluence pages and Jira issues stripped to their substance as markdown, git commits summarized, repo files browsable inline. Enrich each item with the metadata and tags that make it findable, then fold it into a context — so augmentation is a step in composition, not a separate pipeline to maintain.

Consider next