FAQ

Is Memory Layer a vector database?

No. It uses PostgreSQL and can use pgvector, but the product is a memory workflow: capture, curation, evidence, retrieval, briefings, agent integration, and evaluation.

Does it replace documentation?

No. It complements docs by preserving decisions, incidents, project conventions, and operational context that often never reaches README files.

Does it work offline?

The service and deterministic retrieval paths can be local-first. External LLM or embedding providers receive text only when you configure and use them.

Can I use local embeddings?

Memory Layer supports OpenAI-compatible embedding endpoints, which can include local compatible servers when configured.

Can multiple projects share one database?

Yes. Queries and memories are project-scoped. Use clear project slugs and inspect status when moving repositories.

What should become a memory?

Durable project facts, decisions, conventions, fixes, operational lessons, and constraints. Do not memorize transient observations like "I opened a file".

How do I know it works?

Run status and ask a question whose answer should require project context. Inspect citations before trusting the answer.