RL Training Pipeline
Define a reward signal, connect your data, and ship a trained model. No lab relationship required.
Learn about the training pipeline →
The best model for your task isn't GPT or Claude. It's a small model trained specifically for you.
Trusted by engineering teams who need real model performance
Small Model Optimization
Models sized for your task, not for a benchmark leaderboard. Smaller means faster, cheaper, and easier to own.
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Inference Efficiency
Smaller models cost less to run. We treat inference cost as a feature, not a footnote.
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What teams say about training their own models.
"We got quoted $4.5M by a major lab for a fine-tuned model. Freesolo did it for a fraction of that, and the model actually performs better on our specific task. I don't know why we waited so long."
Priya NairCTO, Series B fintech
"We tried to run RL ourselves and spent three months getting nowhere. The tooling assumes you have a research team. Freesolo's pipeline just works — we had a trained model in two weeks."
Marcus DreyerML Engineer, enterprise SaaS
"Everyone told us we needed a frontier model for our use case. We didn't. A small model trained on our data with a proper reward signal beat the big APIs on our eval set and costs 20x less to run."
Tomás VegaFounder & CTO, healthtech startup
"The labs treat RL as a premium service they sell you after you've already committed to their ecosystem. Freesolo treated it as an engineering problem. That distinction matters a lot when you're watching your inference bill."
Dana KimVP of Engineering, enterprise SaaS
"I've talked to four different labs about task-specific training. Every conversation started with 'our minimum engagement is $2M.' Freesolo was the first team that talked to us like it was a normal engineering project."
Olu AdeyemiCTO, logistics startup
"Reward modeling is genuinely hard to get right, but it's not a research problem — it's a design problem. Freesolo understood that immediately. We iterated on our reward signal four times in the first month and each run was meaningfully better."
Rachel OseiHead of ML, Series A startup
Built for real tasks, not benchmark leaderboards
Task-Specific Training
Define a reward signal, connect your data, and ship a model trained specifically for what your product needs to do.
See how training works ↗
RLHF Alternatives
RLHF is not the only path. We help you pick the right feedback mechanism for your task — whether that's preference data, rule-based rewards, or something else entirely.
Read about reward design ↗
Cost Reduction
A small model trained for your task costs a fraction of what the labs charge — and runs cheaper at inference too. That's not a rounding error; it compounds.
See pricing →
Changelog
Mar 11, 2025
Launched reward model evaluation toolkit
Feb 28, 2025
Reduced average training run cost by 40%
Jan 30, 2025
Released open benchmarks for task-specific RL
Jan 14, 2025
Shipped RL pipeline self-serve onboarding
See what's new in Freesolo →
Freesolo is an engineering team that thinks the RL market is broken — and is fixing it.
Work with us
Research & engineering
Why small models beat large ones on narrow tasks
Benchmark performance on general tasks doesn't predict performance on your task. Here's the data behind why we build small and specific.
RLHF without the lab budget
Human feedback loops don't require a research team or a frontier lab contract. We break down what RLHF actually costs and how to run it yourself.
The real cost of training a model in 2024
Companies are being quoted five million dollars for work that costs a fraction of that. We break down where the money actually goes — and where it doesn't need to.
View more posts →
Start training your model.
You don't need a seven-figure contract to get a model that actually works for your task.