Decide
AI Solution Architecture
The technical design for how AI, your data and your existing systems fit together.
The problem
The failure mode is rarely the model. It is that the data lives in four systems that do not talk, nobody has decided where the source of truth sits, and no one has designed what happens when the model is wrong. Skipping this step is how a promising pilot becomes an integration problem eighteen months later.
What we build
- Target state architecture across data, models and integrations
- The integration design against your existing systems
- Data flow and retention design
- The human-in-the-loop and approval model
- Security, access and residency positions
- A cost model at expected volume
How the engagement runs
Two to four weeks, usually straight after strategy or as the opening phase of a build.
What you get
- An architecture document your own developers or another vendor could build from
- An integration map
- A costed running estimate
Where this does not fit
For a single narrow automation with one system and one data source, this is heavier than the job needs. We will tell you if that is what you have.
Related solutions
- AI StrategyWork out where AI actually pays in your business, and in what order to do it.
- Embedded AI LeadershipAn AI lead inside your business on a standing monthly commitment, accountable to your executive team.
- Workflow AutomationThe deterministic plumbing underneath: systems connected, manual steps removed, processes redesigned around what the tooling can now do.
Start with a discovery call.
An hour on how your business runs, where the time goes, and whether AI is worth spending money on yet. You get our read either way.