Stop thinking about embeddings
@turbopuffer is a search database built directly on object storage that handles both semantic and full-text search.

vector and full-text search built on object storage: fast, 10x cheaper, and extremely scalable
@turbopuffer is a search database built directly on object storage that handles both semantic and full-text search.
turbopuffer is a search database built directly on object storage. The system has a single stateful dependency (S3/GCS) and leans heavily into compute/storage disaggregation.
Applied Compute partnered with turbopuffer to show that a small, specialized search model post-trained to use precomputed search indexes can achieve impressive search quality at a fraction of the cost and latency of frontier models.
Point-in-time web search and page fetch over a frozen archive. Query the web as it existed on any past date, reproducibly.
Open-source incremental data framework for AI agents. Keep codebases, docs, and knowledge continuously indexed — fresh context, zero re-processing. Python API.
The Exa Web search API retrieves the best, realtime data from the web for your AI
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