Our Delivered work
Real software, rebuiltas controlled worlds
Every environment below was scoped, architected, populated with synthetic data, quality-checked and handed over. Each is a working surface with its own state, tools, permissions and failure modes, built around a consistent synthetic persona, that an agent can be trained and measured inside.
200+
RL environments delivered by our founding team
Environment types
Computer-use RL · Coding RL · Tool-use RL · Multi-app RL · Multi-agent RL · Gaming RL · Long-horizon RL · Simulation and physical RL
Delivered for teams at
Work delivered by our founding engineering team.
What shipped with each
Handed over whole,not handed off
An environment is only useful if the team receiving it can run, extend and score it without us in the room.
- 01
Environment source and deployment
The application itself, runnable and reproducible.
- 02
Seed data and personas
Synthetic records, histories and accounts that cohere across the workspace.
- 03
Task suites
Single-step through long-horizon work, graded on deliverables.
- 04
Evaluation harness and rubrics
Automated checks plus expert criteria for what counts as done.
- 05
Documentation and handover
How it is built, how it is extended, how it is scored.
- 06
A year of support
Reported bugs and performance issues resolved for twelve months.
Partner with Node-Zero Labs
Build better AI
We build what models need to learn, practise and improve.
Bring us your client’s requirements. We’ll return with a quote, a delivery plan and an exact list of deliverables, scoped to your volume, domains and deadline, so you can commit with confidence.
For AI labs and AI infrastructure companies
Training data · RL environments · Agentic tasks · Evaluations · Expert workflows · Applied AI research