RL environments are the bottleneck for every AI agent company. Trajecta makes them self-serve. Define your workflow, train your agent, deploy it. No ML team required.
Labs spend millions building RL environments to train agents. Enterprises launch agents straight into production with no simulation layer, no stress testing, no controlled training. The result: brittle systems, unpredictable outputs, and AI initiatives that never scale.
Trajecta bridges this gap. The same training discipline that made frontier models reliable, now accessible to every business building with AI agents.
Describe the states, actions, and success criteria of any business process you want to automate.
Trajecta generates a high-fidelity simulation of your workflow, complete with realistic variations and edge cases.
Your agent trains through thousands of simulated episodes, learning optimal strategies through trial and reward.
Deploy an agent that has already mastered your workflow before it touches a single real customer or system.
Agents deployed raw into production. No simulation, no training loop, no verification. Teams discover failures in real-time with real customers. Iteration is slow, expensive, and high-stakes.
Agents trained on thousands of simulated episodes before they go live. Every edge case explored. Every failure mode tested. Production deployment is a graduation, not an experiment.
Train agents on realistic enterprise workflows. Test across CRM, spreadsheets, email, and multi-tool chains. Ship agents that work on day one.
Build the same training infrastructure that frontier labs use, without hiring an RL team. Control what your agents learn. Verify before you trust.
Trajecta is building the infrastructure layer where that training happens. Every workflow has a trajectory. Every trajectory has a better version. We find it.