The short version
Six to eight weeks, if the AI core is built first and the product is scoped to one idea. The number is on the quote, and you see working software every week.
Week by week
| Week | What happens |
|---|---|
| 1 | Scope in writing. Accounts created in your name. The AI core runs on your data with a first accuracy number. First demo. Week-one exit applies. |
| 2 to 3 | Core product screens, authentication, roles. Accuracy measured on every change. |
| 4 to 5 | Payments or billing, admin console, the second AI workflow if there is one. Mid-sprint demo and payment. |
| 6 | Production deploy on your cloud account. Monitoring. Onboarding docs. |
| 7 to 8 | Where needed: polish, a second integration, launch review where the “next” list becomes the retainer roadmap. |
Why the AI core comes first
Most AI MVPs fail on the model, not on the app. If the model cannot read your documents or match your records well enough, no amount of product work fixes that. So the first week is spent proving the core on your real data and publishing an accuracy number. If the number is bad, you have lost a week and a deposit, not two months.
What makes it slip
A second idea. The sprint is one AI core and one product around it. A second idea goes on the “next” list, in writing. Integrations with tools that have no API; we name those on the first call. Slow decisions. The build moves at the pace of your answers; we ask for one decision-maker and about two hours a week.
What you can cut to go faster
Fewer user roles. One payment method instead of three. The admin console as a plain table instead of a dashboard. A single AI workflow instead of two. Each of these takes days off the plan and is a conversation on the first call, not a surprise later.