Trieve provides a complete search + RAG backend as a service — upload document chunks, Trieve handles embedding, chunking, indexing, and search with hybrid dense+sparse retrieval. For agents: POST /chunk to ingest document chunks, POST /chunk/search for semantic/hybrid/full-text search, POST /chunk/generate for RAG-style answer generation over retrieved context, and POST /analytics/search for search performance analytics. Trieve handles embedding model management (supports OpenAI, Cohere, custom models). Self-hosted (Docker Compose) or Trieve Cloud. Early-stage but growing; confidence is docs-derived.: Comprehensive Agent-Usability Assessment
Docs-backedREST API at api.trieve.ai. Chunks: POST /chunk body: {chunk_html: "document text", metadata: {...}, tracking_id: "your-id", tag_set: ["topic1", "topic2"]}. Search: POST /chunk/search body: {query: "search query", search_type: "semantic"|"fulltext"|"hybrid", page_size: 10, filters: {must: [{field: "tag_set", match: ["topic1"]}]}}. Response: {score_chunks: [{chunk: {id, chunk_html, metadata, tracking_id}, score: 0.92}]}. RAG generation: POST /chunk/generate body: {prev_messages: [{role: "user", content: "..."}], chunk_ids: ["id1", "id2"]}. Groups (for document hierarchies): POST /chunk_group creates a group; POST /chunk_group/{group_id}/chunks adds chunks to a group. Datasets: each Trieve project uses datasets (dataset_id in header).