Eval directory
Evals for turbopuffer
7 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for turbopuffer AI products.
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.
How complete this published benchmark library is across datasets, metrics, rubrics, use-case maps, and pack context. This is library coverage, not an agent performance score.
Test datasets
7/7 packs
Scoring metrics
0/7 packs
Judge rubrics
7/7 packs
Use-case maps
0/7 packs
Pack context
7/7 packs
Available eval packs for turbopuffer
7 packs ready to run.
Cache Warmup Billing And Dr
Evaluates turbopuffer's Cache Warmup Billing & DR across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Serverless vector database eval coverage.
Delete And Tombstone Semantics
Evaluates turbopuffer's Delete & Tombstone Semantics across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Serverless vector database eval coverage.
Hybrid Query And Filters
Evaluates turbopuffer's Hybrid Query & Filters across 11 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Serverless vector database eval coverage.
Namespace Isolation And Acl
Evaluates turbopuffer's Namespace Isolation & ACL across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Serverless vector database eval coverage.
Pagination And Export
Evaluates turbopuffer's Pagination & Export across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Serverless vector database eval coverage.
Upsert Durability And Wal
Evaluates turbopuffer's Upsert Durability & WAL across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Serverless vector database eval coverage.
Vector Schema And Distance
Evaluates turbopuffer's Vector Schema & Distance across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Serverless vector database eval coverage.
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.