Agents for industry software
Bring agents trained on industry work back to people who do it. Your team reviews performance and decides how to deploy, alongside existing software or through an integration you approve.
Partner with usPRAEVIDEO / PLATFORM


Industry knowledge. Agent capability.
Gaia turns industry knowledge into environments where AI agents learn real work, connecting software partners to new capabilities and data-licensing opportunities.
Discuss a workflowA completed work order might tell you which part fixed a fault. It rarely tells you everything a technician knew, which options were available, or why another repair would have failed.
Building a useful training environment means reconstructing that context. An agent needs tools it can use, rules it must respect, and a way to check its answer. A pile of exported records is only a starting point.
Gaia brings that work into one process: prepare source material, recreate a task, evaluate attempts, and use failures to guide further training.
HOW WE BUILD
Work with people who know it. Identify inputs, decisions, exceptions, and a result they would accept.
Recreate relevant records, tools, and business rules. Separate training work from live customer systems.
Use checks that reflect actual work: a balanced reconciliation, a feasible schedule, a correctly resolved exception. Keep separate tasks for evaluation.
Compare against a starting model and simpler approaches. Inspect mistakes rather than relying on one aggregate score.
For partners, decide whether an agent is ready for a limited deployment. For buyers, package suitable data, environments, and evaluations under agreed rights.
Bring agents trained on industry work back to people who do it. Your team reviews performance and decides how to deploy, alongside existing software or through an integration you approve.
Partner with usLicense approved data and environments to model developers, AI product teams, and enterprises. Ongoing buyer agreements can generate recurring licensing revenue, shared with software partners on agreed terms.
For AI teamsReview what was tested, what improved, what still fails, and where human review remains necessary. Compare performance against a baseline before deciding how to deploy.
Scope, access, and delivery requirements are agreed for each engagement.