# Knowledge search # Knowledge search Data Builds reusable retrieval agents that answer from a curated document corpus — embeddings, a search index, a knowledge library, schema and header mapping, reuse of prior decisions, confidence thresholds and a human review loop. - **Used when** — When a question should be answered from a defined corpus rather than from a model's general knowledge, and the answer needs a confidence and a reviewer. - **Loads first** - The retrieval-system and agent-building skills. - The shared engineering guidelines. - **Returns** - Whether the use case is retrieval at all, and why. - The reusable agent boundary and its runtime contract. - The corpus and metadata contract. - The retrieval and confidence policy. - The production stack and the local emulation path that replays it. - The human review and learning loop for runtime decisions. - The evaluation and operations plan, and an implementation checklist. - **Hands off** - Search to production — taking a retrieval system from prototype to production ## Others in Data - Counterparty document expectations - Data-lake assistant - Dataset fulfilment - Metric reconciliation - Model curator - Pipeline control panel - Property data exploration - Public record ingestion - Question answering - Report catalog - Search to production