Capabilities
We take responsibility for the whole path — from the integration surface and data foundation through the model layer, the interface, and the controls that keep it accountable in production.
Domain-specific applications where AI is one component of a larger, dependable system — document intelligence, decision support, structured extraction, and operator consoles built for daily use at scale.
Long-running, multi-step processes with tool use, branching logic, and human checkpoints — engineered with explicit state, retries, and escalation paths rather than open-ended autonomy.
The connective work most programs underestimate: reconciling identity, data models, and event flows across SaaS platforms, internal services, vendor APIs, and systems that predate all of them.
The substrate AI depends on — pipelines, warehouses, vector and search infrastructure, lineage and quality controls, deployed into your cloud with your security posture intact.
Measurable behavior before and after release: evaluation suites tied to business outcomes, regression gates in CI, full audit trails, and access controls that satisfy security and compliance review.