Put AI in your product. On purpose.
Find the AI use cases worth building, scope them properly and roll them out, led by people who have taken AI agents to production.
When to bring us in
If two or more of these sound familiar, it’s already costing you time.
The board is asking about AI
You need a clear answer on where AI fits, and what it will and won’t do.
Competitors just launched AI features
You want to respond with something useful, not a gimmick.
Plenty of ideas, no business case
Every team has an AI wish list, but nothing is prioritized or costed.
A pilot worked but never shipped
The demo impressed everyone, then stalled on the way to production.
You’re not sure your data is ready
Nobody can say how much cleanup stands between you and a working feature.
Build, buy or partner?
You need a clear-eyed view of what to build in-house and what to buy.
Pick your starting point
Best first step
AI Adoption Sprint
Identify AI and agent use cases, score them, scope the best one and plan the rollout.
From [YOUR PRICE]
For rollout
Fractional PM for AI
A senior PM to take your chosen AI feature from spec to production.
Quoted on a call
AI Feature Spec Pack
Engineering-ready requirements for an AI feature, with evaluation criteria and guardrails.
From [YOUR PRICE]
How an AI Adoption Sprint runs
Week 1
Discover
Map workflows, pain points and the data you already have.
Week 2
Prioritize
Score use cases on value, feasibility and risk.
Week 3
Scope
Spec the top use case, set success metrics and decide build vs buy.
Week 4
Plan the rollout
Pilot plan, guardrails and the change management your team needs.
Proof, not promises
From our founders’ experience
Taking AI agents to production on a B2B product data platform
From use-case selection to rollout across a global distributor customer base.
[RESULT, e.g. hours of manual work removed]
“He demonstrated an impressive understanding of the project requirements.”
[CLIENT NAME] · Complex documentation project
Questions clients ask
Do we need clean data before we start?
No. Assessing data readiness is part of the sprint, so you’ll know exactly what needs fixing.
Do you build the AI features?
We scope, spec and manage the work. Your engineers or a development partner build it.
Which AI models do you recommend?
We’re vendor-neutral and choose based on your use case, cost and data requirements.
How do you handle risk and compliance?
Guardrails, human review steps and evaluation criteria are built into every plan.