brain-search

To find references in your personal knowledge base, you issue a natural-language query to retrieve relevant stored materials. This semantic lookup surfaces where specific information exists so you can review the most relevant context tied to topics or entities.

The best way to locate prior context from meeting follow-ups is performing a semantic lookup against your stored data. This matches your query intent to existing references, quickly surfacing the relevant materials you need to review.

Yes, you can use natural-language search to retrieve personal data for research. By asking questions tied to vague topics or entities, the system applies intent-matched search behavior to return reference-focused results from your knowledge base.

Knowledge retrieval works effectively for finding information tied to specific entities or topics. It requires intent-matched search behavior driven by defined trigger phrases to successfully locate and return relevant references from your stored brain content.

To get reference-focused results instead of direct answers, you query your knowledge base using defined trigger phrases. This approach locates where the information exists within your stored materials, providing references suitable for your downstream synthesis.

A limitation of semantic lookup for context finding is that it returns references rather than direct synthesized answers. It requires intent-matched search behavior driven by defined trigger phrases to accurately locate prior context tied to topics within your stored data.