What is Patronus AI?

Patronus AI is a San Francisco startup founded by former Meta machine learning experts Anand Kannappan and Rebecca Qian, focused on automatically detecting costly and dangerous LLM mistakes at scale. The company raised USD 17 million in Series A funding led by Notable Capital, bringing total funding to USD 20 million. Patronus AI developed a first-of-its-kind automated evaluation platform that identifies errors like hallucinations, copyright infringement, and safety violations in LLM outputs. The platform uses pay-as-you-go pricing starting at USD 10-20 per 1,000 API calls, with USD 5 in free credits for new users. Trusted by companies like OpenAI, HP, Pearson, AngelList, and Etsy, Patronus AI has processed millions of requests, catching hundreds of thousands of hallucinations. Customers praise the research-first approach and 20% better evaluation performance than competing methods, though as a startup-stage company, many processes are still being built.

Key features

Core capabilities this platform advertises.

Automated LLM evaluation platform
Hallucination detection
RAG-specific evaluation metrics
Red-teaming capabilities
CI/CD integration

Strengths and tradeoffs

What this tool does well, and the limitations to keep in mind.

Pros

20% better evaluation performance than competitors
Trusted by OpenAI, HP, Pearson, and major enterprises
Research-first approach from Meta ML experts
Pay-as-you-go removes barriers to entry

Cons

Very early stage with processes still being built
Startup maturity risks typical of young companies
Integration breadth still developing

Plans & pricing

What's included in each plan, and how the tiers compare.

Pay-as-you-go

$10-20

Per 1,000 API calls

$5 free credits
Smaller evaluators ($10/1k)
Larger evaluators ($20/1k)
Self-service access
API access

Enterprise

Custom

Annual contract

Higher rate limits
Custom evaluation models
Webhooks
AI Professional Services
Custom security
Private deployment

View official pricing page

Common use cases

AI teams that need rigorous, automated quality evaluation and safety testing

Detecting hallucinations in production
RAG quality evaluation
Adversarial testing of LLM systems
Continuous evaluation in CI/CD
Model comparison and selection

Using Patronus AI with Respan

Integrate Patronus AI's evaluation platform with Respan to automatically detect hallucinations, copyright violations, and safety issues in your LLM outputs. Add comprehensive quality gates to AI workflows with research-backed evaluation. With Respan orchestrating Patronus AI alongside your LLM providers, ensure reliable, safe AI applications.

Detect hallucinations automatically with 20% better accuracy
Catch copyright infringement before deployment
Assess model performance across accuracy, safety, and brand alignment
Start with USD 5 free credits for immediate testing

Run Patronus AI in production with Respan

10KFree traces/mo

1,000+Models

5 minSetup

Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.

Try Respan free

Best Patronus AI alternatives & competitors

Top companies in Observability, Prompts & Evals you can use instead of Patronus AI.

Respan

Nested traces for every LLM call, tool run, and agent turn

Patronus AI: Observability, Prompts & Evals