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Evals for turbopuffer

7 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for turbopuffer AI products.

Data Analysis
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About turbopuffer

turbopuffer is a serverless vector database designed for high-performance approximate nearest neighbor search at scale. It handles ingest, indexing, and hybrid queries with a simple HTTP API and charges only for storage and queries — no always-on infrastructure.

Employees

~10

Industry

Vector Database

Headquarters

United States

Available eval packs for turbopuffer

7 packs ready to run.

Why eval turbopuffer AI

turbopuffer's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.

The Corsac eval library for turbopuffer measures four dimensions teams care about most when deploying data analysis agents:

  • Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
  • Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
  • Safety gates — does it escalate or refuse when it should, and only then?
  • Operator quality — does it preserve analyst trust by surfacing the right context at the right time?

Every eval pack above is hand-authored against turbopuffer's public product surface and runnable in Corsac with your own data.