Developer builds graph-based 'company brain' with cited answers and human approval gates

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A developer describes building Recall, a system that stores company knowledge such as incidents, pull requests, decisions, chat messages and people as a connected graph rather than relying on standard document retrieval. The aim is to answer causal questions, like why an incident occurred, by tracing a chain of linked evidence that the system cites at each step. Each person gets an isolated memory graph, and outdated facts are superseded rather than deleted, with erasure requests producing receipts. Before carrying out consequential actions such as database migrations, the agent displays the potential impact and waits for human approval, which is logged in the graph. The demo company, Meridian Pay, uses fictional seeded data, though the FalkorDB instance, queries and agent behavior are real.

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