SID-1 is an agentic search model that is 24x faster than GPT-5.1-high, 374x cheaper than Sonnet 4.5, and achieves 1.9x higher recall than traditional RAG pipelines. Here's how we trained it using larg...
turbopuffer now allows you to combine attribute values into the scoring function of text queries. Ranking by attribute helps achieve better relevance in the first stage with the same scalability chara...
A customer query was taking over 4× longer than it should have. The profiler pointed at Rust code we'd assumed was free. We followed the trail all the way down to assembly to find the true cost.
I analyzed how BM25 query latencies scale with document count and top_k. Longer queries scale less efficiently, and essential terms impact performance in some surprising ways.
turbopuffer has improved text search performance up to 20x by adopting the same text search algorithm as Apache Lucene, a vectorized variant of block-max MAXSCORE
Describing how turbopuffer measures the recall (accuracy) of its vector indexes in production continuously. This ensures that turbopuffer's search results are accurate and reliable, despite using appr...
Inaugural blog post about the development of turbopuffer, a search engine that uses object storage and SSD caching for cost-effective, low latency search. This post describes into the motivation behin...