We have moved from bespoke agent development to factory-model delivery. Reusable engines, standardized pipelines, and quality automation mean every agent benefits from all previous agents.
Two parallel pods delivering 4 agents per month each — giving enterprise programs a predictable, scalable delivery cadence they can plan against.
Every agent we build adds to our engine library and knowledge base — making each subsequent agent faster to build and more reliable to deploy.
Quality gates, evaluation frameworks, and behavioral testing are embedded into the factory pipeline — not reviewed at the end as a manual process.
Factory-delivered agents transition seamlessly into our MLOps and observability framework — production deployment is a factory output, not a separate project.
