AI Architecture & Build-Buy-Partner Decisions

AI architecture determines which capabilities remain proprietary, which models and platforms can be sourced, how data and tools connect, and where control is required for reliability, privacy and economics.

Matchpoint approaches AI as an operating capability with accountable owners, explicit decision gates, measurable acceptance criteria, documented architecture and a practical path from discovery to production.

AI architecture is a sequence of control decisions. We identify which data, prompts, tools, policies, models, retrieval components and evaluation assets create differentiation; which can be sourced; and which interfaces need portability because provider capability and economics will change.

Build, buy and partner options are compared using the same scorecard: time to value, workflow fit, performance against representative tasks, data and privacy requirements, integration depth, observability, operating cost, switching cost, internal skills and roadmap control. Vendor demonstrations are translated into tests using the organisation's own tasks and constraints.

The resulting reference architecture separates business logic and orchestration from model endpoints, documents data flow and permission boundaries, and defines fallbacks for provider, tool and retrieval failure. Architecture decision records capture the evidence, trade-offs and triggers that would justify revisiting each choice.