Better agents start with better environments.
Discover how reinforcement learning environments work, explore real-world use cases, and scope your next agent training or evaluation project.
orders.lookup( #4832 )Every task needs the
right environment.
From coding agents to enterprise workflows, see what a realistic training or evaluation environment needs to get right.
View all 16 categories →Coding RL Environments
Train and evaluate agents that edit, test, and repair real codebases.
Explore category →Browser RL Environments
Simulate web tasks, navigation, forms, and multi-step browser workflows.
Explore category →Computer-Use RL Environments
Test agents operating desktop applications and graphical interfaces.
Explore category →Customer Support RL Environments
Recreate customer conversations, policies, and service operations.
Explore category →Enterprise Workflow RL Environments
Model complex business processes across CRM, ERP, finance, and operations.
Explore category →CRM Agent RL Environments
Train agents to update opportunities, accounts, and sales workflows safely.
Explore category →Start building.
Without the busywork.
Practical browser-based utilities to clarify specifications and reason about verifiable rewards. No API keys, signups, or training claims.
Environment Blueprint Generator
Turn a use case into a structured environment plan with tasks, actions, state, and verification requirements.
Generate a blueprintReward Lab
Explore weighted success criteria, test reward scenarios, and export a starter rubric for your agent workflow.
Open Reward LabBuild for outcomes.
Not just demos.
A useful environment has more than a prompt and a score. It creates a world an agent can interact with, then checks whether the outcome is actually correct.
Understand RL environmentsDefine the objective
What should the agent achieve, and what actions must be prohibited?
Simulate the workflow
Give it tasks, tools, and controlled state in a repeatable environment.
Verify the result
Measure the final state with tests, checks, and realistic failure cases.
Evaluate and improve
Run comparable episodes and use feedback to identify real progress.
Looking for a custom
RL environment?
Describe your agent, intended workflow, and evaluation requirements. We can review the scope and, where appropriate, help connect you with an independent technical specialist.
Good environments begin
with clear thinking.
What is an RL environment?
A practical explanation of tasks, state, actions, rewards, and verification.
Read guide ↗ArchitectureHow to design an RL environment
A scoped checklist for going from business workflow to verifiable tasks.
Read guide ↗FrameworksChoosing an RL environment framework
Understand when to look at Verifiers, NeMo Gym, BrowserGym, or Gymnasium.
Read guide ↗Scoping a custom RL environment for coding, browser, tool-use or enterprise agents? Share your requirements and we will point you to a suitable approach or builder.
Request an environment