An AI sprint that ends with your team running the workflow.
An AI sprint only counts if something ships: this one takes a single workflow from proof of concept to your team running it, in six weeks.
- Duration
- 6 weeks
- Format
- Fixed fee, fixed scope
- You get
- One workflow your team runs

The failure mode this kills
Most AI projects die between the demo and the rollout. The build works, the room nods, and three months later nobody has touched it, because the process never changed and nobody was trained. The sprint exists to make that outcome impossible: it doesn't end at the demo, it ends when your team is running the workflow without us.
How the six weeks run
The roadmap
Weeks 1 to 2Which workflow, what changes, what we measure. The AI implementation roadmap gets agreed before anything gets built.
The build
Weeks 2 to 5Process redesigned, automation built inside your existing stack, tool-agnostic. No platform lock-in.
The handoff
Weeks 5 to 6SOPs written, team trained, results measured against the baseline we set in week one.
What ships
A working workflow your team runs. The SOPs that document it. The training that made it stick. And a measurement baseline with the before-and-after numbers, so the ROI conversation is arithmetic instead of vibes. Want to size the prize first? Run your numbers through the AI ROI calculator.
The 30/70 split in practice
The build is the easy 30%. Most of the six weeks goes to the 70%: redesigning the process around the automation, training the people who run it, and following through until the new way is the normal way. That allocation is why sprint workflows survive contact with month three.
The best sprints start with an AI assessment, which picks the right workflow and credits toward the sprint. After the sprint, teams that want a next workflow every quarter roll into the fractional head of AI retainer.
FAQ
Six weeks. One workflow. Shipped.
The scoping call picks the workflow, sets the fixed fee, and defines what measured success looks like before anything starts.