turbopuffer: The Serverless Search Engine Built for AI Applications

What Is turbopuffer? — Serverless Search for AI

turbopuffer is a serverless search engine purpose-built for AI applications, offering vector and text search with a focus on speed, scalability, and cost efficiency. Unlike traditional search databases that were designed before the AI era, turbopuffer is architected specifically for AI-native applications requiring fast, reliable search at scale.

Key Features and Performance — 20ms Latency at Scale

turbopuffer delivers approximately 20ms p90 latency on 10M documents, making it suitable for real-time AI applications where search speed directly impacts user experience. The serverless architecture means you don't manage infrastructure—turbopuffer handles scaling automatically based on query volume.

Cost Savings: Up to 95% Cheaper — Why It Matters

The company claims turbopuffer is up to 95% cheaper than traditional vector/text search databases. For AI applications that require extensive search operations, this represents massive cost reduction. The economics enable even small teams to build sophisticated AI search features without enterprise budgets.

Who's Using turbopuffer? — Customer List Shows Quality

Notable customers include Cursor, Notion, Linear, Cognition, Atlassian, Ramp, Granola, and Legora. These are demanding technical companies that have evaluated alternatives and chosen turbopuffer for production workloads. The customer list validates turbopuffer's technical claims.

Common Questions About turbopuffer

Q1: What makes turbopuffer different from traditional vector databases? A1: turbopuffer is built specifically for AI-era workloads with serverless architecture, achieving ~20ms p90 latency and up to 95% cost savings compared to traditional solutions.

Q2: How does serverless help AI applications? A2: Serverless means automatic scaling based on query volume without infrastructure management, ideal for AI applications with variable or growing search demands.

Q3: Is turbopuffer production-ready for large-scale applications? A3: Yes, companies like Cursor, Notion, and Atlassian use it for production workloads, proving it handles demanding technical requirements.

Q4: How can I get started with turbopuffer? A4: New users can sign up and run their first query in approximately 4 minutes according to turbopuffer's documentation.

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