8-Week AI Production Sprint
One AI workflow. In production. In eight weeks.
Most AI programs stall in a notebook, a vendor demo, or a steering committee. This sprint takes a single, named workflow — document intake, support assist, operations summary, or qualification — and makes it a product your staff can log into.
Limited intake. If the use case is theatre, we will say no and recommend Paid Discovery instead.
Production login
Human review queue
Audit log
Fallback path
A pilot is not a product
A model that works on ten sample files is not an operating system. Production means authentication, permissions, a queue for exceptions, logging, cost control, and a person who knows what to do when the model is wrong.
What you get in eight weeks
One locked workflow, written before Day 1.
Application shell: login, roles, the queue, the result screen.
The model or API call, with human review on low confidence.
Logging, basic evaluation, and a fallback that does not dump the user.
Deployment to the agreed environment and a two-week stabilization window.
Apply for the AI sprint
→This is not a company-wide AI transformation. It is not model research. It is not five workflows in parallel.
Eight weeks, on purpose
Week 1–2
Lock the workflow, data path, success bar, and review rule.
Week 3–5
Build the product around the model: queue, permissions, integration.
Week 6–7
Test with real examples. Fix the failure cases that matter.
Week 8
Production, handover, stabilization start.
Fit
A fit
You can name one workflow.
You have example data.
Someone on your side can review outputs.
You want staff using it, not another proof-of-concept video.
Not a fit
You want a foundation model of your own.
You cannot describe the job.
You need a regulated clinical diagnostic.
You want “AI everywhere” in two months.
If the workflow is real, we can put it in production.
We use this application to see whether the program is a fit. It is not an acceptance. Privacy Policy.