Capability · Build
Production systems, not prototypes: integrated, evaluated, observable and owned.
The practice that takes an AI use case from prototype to production. It runs inside your operations, with the reliability your teams expect from any other system.
What it includes
Scope of the capability
- System architecture and integration design
- Knowledge and retrieval systems
- Document processing pipelines
- APIs, connectors and event flows to systems of record
- Security, access control and secrets management
How we work
The engineering stance
- Minimum sufficient architecture: the simplest design that meets business, scale, security and compliance requirements.
- Deterministic code where the rules are known; models only where judgment is required.
- Model-agnostic by design: providers and models are swappable behind evaluated interfaces.
Technical notes
- Typed contracts between components and models
- Evaluation sets versioned alongside the code
- Tracing of every model call with cost and latency
Where it applies
Solutions that rely on it
Next step
Where would an intelligent system change your operation first?
Start with an AI Opportunity Sprint, or book a 30-minute conversation about the process you have in mind.