Custom RL environments, engineered to your spec.
Training agents takes more than a reward hack on a generic benchmark. We build reinforcement learning environments and harnesses around your exact training goal, with verifiable rewards and reproducible evaluation.
What we build
An RL harness is the whole loop: the task distribution, the environment the agent acts in, the reward logic, and the evaluation that tells you whether training worked. We design and implement all of it to your requirements.
- Task environments. Web tasks, tool use, coding tasks, multi step workflows, games, or simulations of your own product.
- Reward functions. Verifiable, programmatic rewards wherever possible, so training signal is not noise.
- Evaluation suites. Held out task splits and scoring harnesses you can rerun on every checkpoint.
- Stack integration. Delivered to plug into your training framework, with documentation your team can build on.
How we work
You describe the capability you want the model to learn. We propose a task design, build a working prototype, and iterate with you on reward quality before scaling up the full environment.
Everything is delivered privately, with source code and docs. Payment is in crypto, and the engagement stays between us.
Common questions
Can you build environments for LLM agents?
Yes. Tool use, browsing tasks, code execution, and multi turn workflows are the most common requests we get.
Do you also supply task data?
Yes. Task sets, seeds, and scenario data can be part of the same engagement. Email data@nexorpus.com with what you have in mind.
Who owns the harness?
You do. Full source and documentation are delivered as part of the project.
Describe the data. We deliver it.
One email is all it takes. We reply with questions, samples, and a quote that beats the market.
data@nexorpus.com