AI readiness & workflow sprint
In two to three weeks: your workflows mapped, the one or two worth automating picked, and a working pilot built with evals and guardrails, so you know what AI can do for you before committing to a build.
From a map of the work to a working pilot
Map your workflows
Across engineering, sales, product and operations: what happens today, where the time goes, and where a mistake would hurt.
Pick one or two
Ranked by time saved, risk and effort, and agreed with you before anything is built.
Build a pilot
A working version on a sample of your real data in a test environment, with evals and guardrails from the start.
Review and plan
A data and security review of the pilot, then a rollout plan for taking it to production.
What you get
- A ranked map of your workflows and where AI could help
- A working pilot for the one or two workflows picked
- The eval set and the pilot’s results against it
- A data and security review of the pilot
- A rollout plan: what it takes to go live, expected running costs, and who owns what
Not included
- Production rollout, which is a separate Build engagement
- Integrating every system you run
- Training or fine-tuning your own model
- Organisation-wide AI training (see AI-native teams)
Duration
Two to three weeks, depending on how many workflows we map and the data the pilot needs.
Price
On request. Fixed and agreed in writing before the sprint starts.
Is this the right fit?
Teams that want to use AI but aren’t sure where it would pay off, and teams with an idea they want proved on real data before committing to a build. The sprint is the usual first step into AI workflows & automation.
Common questions about the sprint
What do you need from our team?
A sponsor who can make decisions, a few hours with the people who do the work today, and a sample of real data for the workflows we pick. We agree the times up front so the sprint fits around your week.
What data do you use, and is it safe?
Only a sample of the data the chosen workflows need, agreed with you before we start. It stays in a test environment, and we check how each AI provider stores and uses it as part of the data and security review.
What if no workflow is worth automating?
Then we say so, and explain why. You still keep the ranked workflow map, which shows where AI could help later and what would need to change first.
Which AI models do you use?
Whichever passes the evals for your workflow at a cost and speed that make sense. We often compare more than one model during the pilot, and the rollout plan explains the choice.
Can the pilot go live after the sprint?
Not as it stands. The pilot proves the workflow on a sample of your data in a test environment. Taking it to production is a separate Build engagement, scoped and priced from the rollout plan.
Start with an honest look at what you run
Tell us what you're running today and where it hurts. We'll come back with the two or three changes worth making first — and if the answer is that your setup is fine, we'll say that instead.