Recover incident knowledge with RAG
Support teams accumulate useful decisions across tickets and documents, yet finding them depends on remembering where to look. An internal proof of concept explored retrieval-augme
Why this matters
Software operations improve when decisions are tied to real delivery constraints
These resources help technical leaders make clearer decisions about software modernization, delivery constraints, continuity, and operating risk.
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A guide to move from the decision to the operating criteria and next step without losing the thread.
Support teams accumulate useful decisions across tickets and documents, yet finding them depends on remembering where to look. An internal proof of concept explored retrieval-augmented generation (RAG) over documentation and a legacy PHP/MySQL incident system using Azure AI services. The goal was to retrieve relevant passages and provide source-backed answers, not to train a new model or automate decisions.
From exploration to verifiable delivery
Authorized sources → corpus preparation → permission-aware retrieval → cited answer → review or abstention. Before expanding the pilot, teams must validate coverage, access control, answer quality and index maintenance. Production deployment and measured accuracy have not been established.
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