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What is Patronus AI?

Patronus AI is a research lab focused on the data and simulations that frontier AI models learn from. Its main offering is a catalog of reinforcement learning environments covering software engineering, computer use, customer service, and finance, each built to reflect how real applications behave rather than idealized versions of them. Agents receive tasks inside these simulated applications and are scored with reward signals, giving AI labs a way to improve performance on long, multi-step workflows. The company is also developing Digital World Models, which predict the behavior of digital environments and allow training environments to be generated at scale instead of being built one at a time by hand. These environments and models support the post-training and evaluation of AI agents that operate in software.

What is Composer 2.5?

Composer 2.5 is Cursor’s newest AI-powered coding model, designed to significantly improve software development productivity through stronger reasoning, enhanced collaboration, and better handling of complex engineering tasks. Compared to Composer 2, the new release delivers major gains in sustained coding performance, allowing developers to work on larger and more complicated projects with improved reliability. The model was trained using expanded compute resources, more advanced reinforcement learning environments, and additional optimization techniques focused on both intelligence and usability. Cursor also refined behavioral aspects of the AI, including communication style and effort calibration, to make interactions feel more natural and productive during real-world coding sessions. A major feature of Composer 2.5 is its targeted reinforcement learning system with textual feedback, which provides localized corrections during training when the model makes mistakes such as invalid tool calls or style violations. This approach helps the AI understand exactly where errors occur and improves its decision-making more effectively than broad reward signals alone. The company further strengthened the model by training it on 25 times more synthetic coding tasks than Composer 2, exposing it to a wider range of difficult engineering challenges and edge cases. These synthetic tasks included feature deletion exercises where the model had to reconstruct missing functionality in real codebases using automated tests as validation signals. During large-scale training, Composer 2.5 demonstrated advanced problem-solving capabilities by reverse-engineering cached data and decompiling Java bytecode to recover deleted APIs in synthetic environments. Cursor also implemented sophisticated distributed training systems such as Sharded Muon and dual mesh HSDP, allowing efficient optimization across extremely large AI models and infrastructure clusters.

Media

Media

Integrations Supported

Integrations Supported

C
CSS
Cursor
Dart
Go
Grok Build
HTML
Kotlin
Kubernetes
Lua
PHP
Python
Ruby
Rust
SQL
Scala
Solidity
Swift
TypeScript
XML

API Availability

Has API

API Availability

Pricing Information

Custom pricing based on project scope. Contact Patronus AI to discuss.

Pricing Information

$0.50/M input
$0.50/M input and $2.50/M output tokens
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS
Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Patronus AI

Date Founded

2023

Company Location

United States

Company Website

www.patronus.ai/

Company Facts

Organization Name

Cursor

Date Founded

2022

Company Location

United States

Company Website

cursor.com

Categories and Features

Artificial Intelligence

Machine Learning
Natural Language Processing

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

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