Patronus AI

Industry-first automated evaluation and security platform for LLMs.

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Last verified April 24, 2026

About Patronus AI

Patronus AI provides an automated platform for evaluating and securing large language models (LLMs), enabling enterprise teams to score performance, generate adversarial test cases, benchmark models, detect hallucinations, PII leakage, and other failure modes across 50+ categories. Key differentiators include proprietary evaluator models like Lynx for hallucination detection outperforming GPT-4o, domain-specific benchmarks such as FinanceBench and EnterprisePII, and agent tracing for 15 error modes. Typical buyers are AI engineers and enterprises like Etsy, Pearson, AngelList in saas-technology and financial-services deploying production AI systems. Raised $20M total funding, with $17M Series A in 2024.

Framework coverage

Not yet catalogued. We only list frameworks when Patronus AI publicly documents coverage in their own materials. If you work at Patronus AI and want to add citations, use the correction link at the bottom of this page.

Capabilities

Features Patronus AI markets publicly. Inclusion means the capability is documented — not that it's best-in-class.

LLM Evaluation

Systematic testing of LLM outputs for correctness, relevance, safety, and consistency using automated scorers, rubrics, or human review.

LLM Red Teaming

Automated adversarial testing of LLMs for jailbreaks, prompt injection, and unsafe outputs.

Risk Assessment Workflow

Guided workflows for completing AI impact assessments, risk scoring, and approval routing.

Model Monitoring

Production monitoring for performance, drift, data quality, and fairness regressions.

Agent Tracing

End-to-end visibility into multi-step LLM agent runs: tool calls, intermediate reasoning, token usage, latency, and errors at each step.

Bias & Fairness Testing

Automated statistical testing for disparate impact across protected attributes, with audit-ready reports.

LLM Guardrails & Content Filtering

Runtime guardrails that block or redact unsafe prompts and responses in production LLM applications.

Integrations

Documented by Patronus AI in public product materials.

  • Hugging Face
  • NVIDIA
  • MongoDB
  • Databricks
  • OpenAI API

Pricing

Contact for pricing

Developer tier starts with $10 free credits; API at $10/1k small evaluator calls; Enterprise unlimited custom.

Pros and cons

Pros

  • Proprietary evaluator models like Lynx outperform leading LLMs on hallucination detection.
  • Domain-specific benchmarks including FinanceBench and SimpleSafetyTests.
  • One-line code integration for evaluations.
  • Used by enterprises like Etsy, Pearson for production AI.

Cons

  • Homepage emphasizes simulation research over core eval product.
  • No public documentation of major compliance frameworks like NIST AI RMF.
  • Enterprise pricing not publicly listed.
  • Some conflicting HQ reports (SF vs Dublin CA).

Frequently asked

What is Patronus AI?+

Automated platform for LLM evaluation, security, and optimization with evaluators, experiments, logs, and traces.

How much are API calls?+

$10 per 1k small evaluator calls, $20 per 1k large, $10 per 1k explanations.

What are key benchmarks?+

FinanceBench for finance QA, EnterprisePII for PII detection, SimpleSafetyTests for safety risks.

Is there a free tier?+

Developer tier with $10 free credits, no credit card required.

Sources

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