Services → AI System Design

AI System Design

Production-grade AI architecture before a single line of code.

◆ Architecture-first, not code-first

What you get

"A specification you can build from."

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System architecture document
Complete technical specification covering data flows, model selection rationale, integration points, API contracts, and scaling strategy.
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Data flow and integration spec
Detailed mapping of how data moves from source systems through the AI layer and back to business processes.
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Risk register
The top technical and operational risks in the proposed design, with mitigations embedded in the architecture.
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Build specification
Engineering-ready documentation sufficient to brief an internal team or issue a vendor RFP.

Who it's for

CTO

Responsible for building the system. Needs a design specification that holds up under engineering scrutiny and can be handed to a team.

CDO

Accountable for delivery. Needs architecture decisions documented before development starts — not inferred after it ends.

ENG

Leading the build. Needs unambiguous specifications for data, models, integrations, and performance targets.

What comes next

Infra Review

Verify that your infrastructure can support the system architecture you've just designed.

Risk-by-Design

Embed governance controls into the architecture before build begins.

Tech Feasibility

Haven't validated that the system is buildable at the assumed cost? Do this before Design.

Every engagement starts with a short conversation. No commitment, just specifics.