Search
Get a succinct, token-optimized answer in natural-language markdown, with explainability, source citations, and matching entities.
Accepts either a Cala QL expression or a natural-language question as input — both produce the same response shape.
Examples:
{"input": "What are the biggest AI startups in Europe by funding?"}
{"input": "Who founded Stripe and what is their background?"}
{"input": "What regulations affect fintech companies in the EU?"}
Use this when you want a natural-language answer with sources and explainability. Use knowledge_query when you want structured, tabular rows instead. Use entity_search if you just need to find an entity by name.
Authorizations
Body
Response
Successful Response
The answer to the user's input with the reasoning steps and the context that support the answer.
A succinct answer to the user's input in Markdown format.
"**Altano Energy (Spain)** — Madrid-based, developing renewable energy projects across Spain. Altano secured €60M Series C in 2025 from M&G Investments and Pioneer Point Partners."
A list of reasoning steps to get to that answer.
A list of facts that support the answer.
Entities identified in the answer.