Today’s agents work across filesystems, docker containers, customer repositories, databases, services, and tools. While a trace gives a full agent lifecycle, testing a request requires more: the agent needs to run the task again with the code, data, tools, and services it had the first time.
Today we’re introducing NeoSigma Environments: a playground for agents to replay, explore, and learn from experience.
To work autonomously, agents need a way to verify their own work. Tools and reward signals become useful when an agent can act in a real environment, observe the results, and try again.
NeoEval turns failed production sessions into replayable tasks, graded with your own verifiers. NeoSigma Environments gives those tasks a place to run. Together, they provide a test and training bed for evaluating and optimizing agents against the outcomes that matter to your business.