We build a simulation of your task, score outcomes by your rules, and train the model inside your environment. You keep the weights.
Click a stage to see what happens there and what we deliver for it.
1 · Environment
A simulation of your task: the orders, documents or tickets, the rules, and what counts as done.
We build it from your real cases, with your limits written in: discount caps, approval steps, what must go to a person.
01
Your cases
Past emails, documents, decisions
02
Train
RL in the environment above, or fine-tuning on your data
03
Evaluate
Held-out cases your team marks
04
Deploy
In your environment, with the audit log on
A quote within limits, a request routed to the right owner, a figure that matches the source. If your team can say whether a result is right, we can score it.
Hundreds of similar decisions a week. The environment replays them with your limits written in, so the model trains on your pattern, not a public one.
Training runs on your GPUs or in a private cloud operated only for you, on open-weight models. The weights are yours.
01
Environment
We build a simulation of the task from your real cases: inputs, the rules, what counts as done, and what must go to a person.
02
Reward
Your acceptance criteria become scoring code. The model is graded by your rules.
03
Training
Reinforcement learning in the environment, or fine-tuning on your labelled cases when that is enough.
04
Evaluation and deployment
Held-out cases your team marks. Then deployment in your environment with the audit log on, the same way as the products.
Available
A first process, a product pilot, or a pricing question.
Twenty minutes is enough to know whether it fits.
hello@deverboost.com
NDA on request
We respond within 1 business day