Prime Intellect is an AI infrastructure company building the Open Superintelligence Stack — a full-stack platform that enables organizations and developers to train, deploy, and continuously improve their own frontier AI models, with a strong focus on self-improving agentic systems.

Core Offering
The platform integrates compute, training, evaluation, inference, and sandbox environments into a unified solution. It allows teams to own and optimize their own intelligence by training models directly on proprietary data and workflows, moving beyond reliance on external closed-source models.

Key Capabilities

– RL Environments Hub
A community-driven repository with 2,500+ open RL environments. It enables users to turn any task into a trainable RL environment using the open-source Verifiers library and Prime CLI for seamless init-develop-eval-push workflows.

– Hosted Training (Lab)
A scalable post-training platform optimized for agentic workflows. Supports large-scale reinforcement learning across thousands of environments, with managed pipelines, full visibility, and expert support. Powered by the open-source Prime-RL framework for efficient asynchronous RL at scale.

– Evaluations
Infrastructure-free hosted evaluation service for benchmarking 100+ open-source models, running custom evals, and maintaining leaderboards to drive continuous improvement loops.

– Inference & Deployment
Dedicated deployments, LoRA adapter serving, and OpenAI-compatible serverless APIs. Designed for production use with native support for turning real-world traces into training data, enabling continuous learning where training and inference converge.

– Compute
Flexible GPU access ranging from single nodes to large distributed clusters, with high-performance networking and enterprise-grade orchestration.

Technical Highlights
– Open-sourced models (INTELLECT series) trained via large-scale RL, achieving state-of-the-art performance in their size class across math, code, science, and reasoning benchmarks.
– Active research in long-horizon agents, Recursive Language Models (RLMs), world modeling, automated AI research, and continual/online learning.