Forward Deployed Reinforcement Learning
Osmosis helps companies create task-specific models that beat foundation models at a fraction of the cost.
Use Cases
Use Cases
Build domain-specific extraction models to capture the exact structure and content for any document.
Osmosis offers the schema precision to get data from point A to B.
Use Cases
Teach AI agents to use the exact tools they’ll have in production. Osmosis powers AI agents that stay reliable, even in the most complex multi-step, multi-tool tasks.
Use Cases
Use Osmosis to train specialized coding models for blazing fast generation of domain-specific languages, front-end components, and context-aware tests.
Use Cases
Platform Details
Hands on Deployments
We work directly with customers to support the entire post-training workflow - from feature engineering to reward function creation. We ensure model performance and adherence to customer specifications through being hands-on with the model training & serving process.
Platform Details
Reinforcement Fine-Tuning
Osmosis is a comprehensive post-training platform that allows engineers to leverage cutting-edge reinforcement learning techniques (GRPO, DAPO, etc.) and capabilities (multi-turn tool training) without any of the infrastructure headache.
Platform Details
Continuous Improvement
We integrate with your evaluation solutions to monitor performance and automatically start re-training runs whenever - without the need for an engineer in the loop. We can ingest real-time data and update your models in as little as every hour.
Use Cases
Use Cases
Build domain-specific extraction models to capture the exact structure and content for any document.
Osmosis offers the schema precision to get data from point A to B.
Use Cases
Teach AI agents to use the exact tools they’ll have in production. Osmosis powers AI agents that stay reliable, even in the most complex multi-step, multi-tool tasks.
Use Cases
Use Osmosis to train specialized coding models for blazing fast generation of domain-specific languages, front-end components, and context-aware tests.
