RecallOps Uses AI Memory Layer to Turn Resolved Incidents into Reusable Knowledge

A five-person team built RecallOps, an AI-powered incident-response tool designed to preserve operational lessons after incidents are resolved. The system uses a memory layer called Hindsight, which supports two key operations: retaining resolved incidents as searchable knowledge and recalling relevant past incidents during new investigations. Retention is a deliberate, separate step — an incident must be fully resolved with a confirmed root cause before it can be stored as memory, preventing unverified guesses from polluting future recall. When a new incident is investigated, the system queries Hindsight for pattern-matched past cases, with a fallback to its own database if the memory layer is unavailable. The approach addresses a common engineering problem where post-incident knowledge gets buried in closed tickets or lost entirely, forcing on-call engineers to repeatedly start from scratch.