Imagine handing a detective a warehouse full of documents and asking, "Who committed the crime?" That's the challenge when raw logs meet an LLM, volume without context is just noise.
So we built the Incident Dossier.
Instead of flooding the model with data, our system assembles a structured briefcase: the relevant logs, the suspected service, a timeline of events, the surrounding code context, a preliminary domain hypothesis, and a refined RCA analysis. Everything the AI needs to reason clearly, nothing it doesn't.
In Part 3, we walk through how this dossier comes together using a real FRR BGP bug as the test case, and why curated context beats raw volume every time.
Download Part 3 to see how structured artifacts turn incident data into answers.
