Start here for the decision-making essentials: what Patronus AI does, who it is for, how it is accessed, and the first-party sources behind this profile.
PricingCurrent signal
$10 / 1k small evaluator API calls
Platforms
Percival (Core Platform)RL Envs (RL Environments)
API accessNot public
FoundedNot disclosed by source
AvailabilityWeb / remote
LicenseLynx is freely available on Hugging Face.
Best suited to
Source-backed fit
AI teams building and evaluating agents on coding, dialogue, research, and… Enterprises needing LLM safety, accuracy, hallucination, and… Customer service teams evaluating chatbots on quality, retrieval,… Financial services teams detecting LLM hallucinations using FinanceBench Organizations requiring on-prem or dedicated VPC AI evaluation infrastructure
AI infrastructure · Tool
Patronus AI
Decision-ready
Patronus AI develops simulation research and infrastructure to accelerate progress toward human-aligned AGI. It offers digital world models and AI evaluation/benchmarking tools across software development, customer service, finance, research science, and product applications.
Short answers to the questions buyers and builders commonly ask about Patronus AI. Each answer cites the shared ledger below, where every source is listed once.
01What does Patronus AI say it can do?
Offers digital world models leading on coding, dialogue, research, and general tool use · Designing scenarios that target core model skills to uncover learning signals (Deep Resear · Custom eval model fine-tuning and eval dataset generation (AI Services) · AI evaluation, benchmarking, and development support testing for safety, accuracy, relevan
Patronus AI offers digital world models leading on coding, dialogue, research, and general tool use across public benchmarks
Software development — delivering software across many tools, services, and frameworks · Customer service — handling complex customer support cases end-to-end · Finance — M&A, private equity, quantitative trading, and strategic finance · Research science — exploring research comprehension, synthesis, and extension
Software Development Delivering software across many tools, services, and frameworks
03What should teams verify before adopting Patronus AI?
Base plan limits: 2-week data access, 2 Projects, 5 Experiments per Project, with Logs and
Patronus Experiments Access to last 2 weeks 2 Projects 5 Experiments per Project Patronus Logs Access to last 2 weeks Patronus Traces Access to last 2 weeks
This profile connects the jobs Patronus AI is described as handling with its delivery model, access options and the subjects used to match it to related products in this directory.
Common use cases
Software development across many tools, services, and frameworks
Customer service: handling complex support cases end-to-end and evaluating chatbots
Finance: M&A, private equity, quantitative trading, and strategic finance
Research science: comprehension, synthesis, and extension of research
Product applications: navigating UI/UX across web and mobile
Catching LLM mistakes at scale across existing and custom language models
$10 / 1k small evaluator API calls · $20 / 1k large evaluator API calls · $10 / 1k eval explanations · $10 in free credits to get started
API
Not publicly listed
Source links
14 recorded
Source-backed
Verified facts
Updated September 6, 2026
Each fact points to a recorded source, making it easy to distinguish verified product information from claims that need checking.
Official website
HTTP 200 verified twice
First-party description
Patronus AI | Simulating the World's Intelligence
Source-supported facts
Mission: develop simulation research and infrastructure to accelerate progress toward huma · Offers digital world models leading on coding, dialogue, research, and general tool use ac · Benchmarks covered: InterCode, τ-bench, BFCL-v4, Toolathlon, SpeedrunBench, FinanceBench
Mission
Develop simulation research and infrastructure to accelerate progress toward human-aligned AGI
Capability
Offers digital world models leading on coding, dialogue, research, and general tool use
Benchmark
InterCode, τ-bench, BFCL-v4, and Toolathlon
Use case
Software development: delivering software across many tools, services, and frameworks
Use case
Customer service: handling complex customer support cases end-to-end
View 32 more verified facts
Use case
Finance: M&A, private equity, quantitative trading, and strategic finance
Use case
Research science — exploring research comprehension, synthesis, and extension
Use case
Product applications: navigating UI/UX across web and mobile applications
Capability
Designing scenarios that target core model skills to uncover learning signals (Deep Research, Multi-Turn Dialogue, Long Horizon, Memory)
Practical capabilities
What it helps with
8 documented areas
A concise view of the jobs, capabilities and integrations described in the recorded product sources.
Use case
Software development across many tools, services, and frameworks
Use case
Customer service: handling complex support cases end-to-end and evaluating chatbots
Use case
Finance: M&A, private equity, quantitative trading, and strategic finance
Use case
Research science: comprehension, synthesis, and extension of research
Use case
Product applications: navigating UI/UX across web and mobile
Use case
Catching LLM mistakes at scale across existing and custom language models
Use case
FinanceBench-based LLM evaluation to detect hallucinations on financial questions
Use case
Software development — delivering software across many tools, services, and frameworks
Availability
Where it runs and where to get it
Source checked
Documented product formats, platforms and official distribution destinations. Availability can vary by region and plan.
Cost / license
$10 / 1k small evaluator API calls · $20 / 1k large evaluator API calls · $10 / 1k eval explanations · $10 in free credits to get startedLynx is freely available on Hugging Face.Lynx is freely available on Hugging FaceSpeedrunBench dataset publicly released on Hugging Face as PatronusAI/speedrunbench
Application types
Digital World Model for AI Agent Training and Simulation
Origin
Team of AI researchers and engineers formerly from Meta AI, Amazon AGI, and Google
Platforms
Percival (Core Platform)RL Envs (RL Environments)
Implementation details
Adoption notes
DeploymentOn-prem / dedicated VPC available · Infrastructure managed on AWS
LicenseSpeedrunBench dataset publicly released on Hugging Face as PatronusAI/speedrunbench
Model supportPercival
Data controlCustom data retention and SSO · Does not train models on customer data · Does not share customer data with foundation model companies such as OpenAI
Learning curveIntermediate
Primary use casesSoftware development across many tools, services, and frameworks, Customer service: handling complex support cases end-to-end and evaluating chatbots, Finance: M&A, private equity, quantitative trading, and strategic finance, Research science: comprehension, synthesis, and extension of research, Product applications: navigating UI/UX across web and mobile, Catching LLM mistakes at scale across existing and custom language models, FinanceBench-based LLM evaluation to detect hallucinations on financial questions, Software development — delivering software across many tools, services, and frameworks, Customer service — handling complex customer support cases end-to-end, Finance — M&A, private equity, quantitative trading, and strategic finance, Research science — exploring research comprehension, synthesis, and extension, Product applications — navigating UI/UX across web and mobile applications, Catching LLM mistakes at scale; testing existing and custom language models, Financial Services use case supported, Customer service chatbot evaluation for quality, context retrieval, hallucination, summari, LLM evaluation against FinanceBench on the Patronus AI platform to detect hallucinations o
What to verify before adopting
Base plan limits: 2-week data access, 2 Projects, 5 Experiments per Project, with Logs and
Evolution and major updates
Patronus AI timeline
A concise history of software releases and material product changes. Events appear only when a dated source supports what changed.
Research in progress
Scheduled for research
Building a reliable release history.
This profile is being checked for dated releases and material product changes. Nothing appears here until the exact date and event can be verified from a recorded source.
Dated event Short explanation Original source
Citation ledger
Recorded sources
14 unique pages
Facts, answers, structured details, milestones and primary resource links cite this shared ledger. Each external page appears once; release tags from the same GitHub project are grouped under one release history.
These tools share a workflow, capability or audience with Patronus AI. They may complement it rather than replace it, and are not presented as integrations or endorsements.
Patronus API (optional add-on) for evaluator calls and eval explanations
Pricing
$10 / 1k small evaluator API calls
Pricing
$20 / 1k large evaluator API calls
Pricing
$10 / 1k eval explanations
Pricing
$10 in free credits to get started
Deployment
On-prem / dedicated VPC available
Security
Custom data retention and SSO
Integration
Webhooks (Premium Platform Features)
Capability
Custom eval model fine-tuning and eval dataset generation (AI Services)
Limitation
Base plan limits: 2-week data access, 2 Projects, 5 Experiments per Project, with Logs and Traces limited to last 2 weeks
Company
Patronus AI, Inc.
Use case
Catching LLM mistakes at scale; testing existing and custom language models
Platform
Percival (Core Platform)
Platform
RL Envs (RL Environments)
Security
Does not train models on customer data
Security
Does not share customer data with foundation model companies such as OpenAI
Deployment
Infrastructure managed on AWS
Funding
$50M Series B announced June 25, 2026
Application type
Digital World Model for AI Agent Training and Simulation
Use case
Financial Services use case supported
Support
General contact available at contact@patronus.ai
Support
Security contact available at security@patronus.ai
Company
Patronus AI, Inc.
Mission
Develops simulation research and infrastructure to accelerate progress toward human-aligned AGI
Use case
Customer service chatbot evaluation for quality, context retrieval, hallucination, summarization, and safety
Capability
AI evaluation, benchmarking, and development support testing for safety, accuracy, relevance, behavior alignment, and multimodal use cases
Use case
LLM evaluation against FinanceBench on the Patronus AI platform to detect hallucinations on financial questions
Capability
Multi-step evaluation: assessing appropriate planning, delegation, and execution behaviors required for task completion
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