For businesses whose AI isn't paying for itself yet
Your AI should be paying for itself by now.We make it.
Diagnosis, rescue and delivery for teams whose AI adoption stalled. Working results in weeks — measured in your P&L.
Three fixed-price ways in.
One of them fits. Prices in USD · We work worldwide.
Build — at PRTOTYPE.COM
An idea that needs to exist? Clickable prototype in days, production builds when you're ready.
Learn moreNow at Boffin HubLearn — at Boffin Hub
Your people, coached 1-to-1 on Claude — Code, Design and Cowork.
Learn moreFix — you're in the right place
AI that isn't paying for itself? Start with the AI Reality Check: $2,500 fixed, two weeks, a verdict on everything you run — keep it, fix it, or kill it. Fee credited against your first sprint.
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Our impact in numbers
AI didn't fail you. The delivery did.
MIT studied hundreds of corporate AI deployments and found 95% of pilots show no measurable P&L impact. Not because the technology doesn't work — because of unclear success metrics, poor integration into real workflows, and nobody running it like a proper project. The same research found external specialists succeed at roughly three times the rate of internal builds.
Delivery is what we've done for twenty years — through ERP, cloud, mobile, and every wave where businesses bought the tool and skipped the discipline. The pattern is the same. So is the fix.
How we un-stall AI
Audit what you have
Every tool, licence, pilot and quiet workaround — inventoried and priced.
Pick the one that pays
One use case, chosen by return, not by hype.
Ship it properly
Into the real workflow, with an owner, a deadline and a metric.
Prove it in the numbers
Baseline before, dashboard after. If it didn't pay, we say so.
The Hidden Cost of Half-Adoption
You're already paying for AI. Are you getting paid back?
Unused licences
Industry-wide, roughly two-thirds of paid AI seats go unused. Yours are on the bill either way.
The stalled pilot
It demoed well. It never met a customer. It's still quietly costing money.
Shadow AI
Your team already uses AI daily — their way, on their accounts, with your data.
No success metrics
Nobody agreed what 'working' meant, so nothing can ever have worked.
Tool sprawl
Five subscriptions, three of them doing the same job badly.
Competitors who shipped
The gap isn't who adopted AI. It's who got it into production.
Stalled vs Shipped
The difference isn't the technology. It's whether anyone ran it like a project.
Stalled
Where you might be now
Licences without usage
paying monthly for tools nobody opens.
Pilots without production
demos that never touched a real customer.
Spend without measurement
nobody can say what any of it returned.
Shipped
Where we get you
One working deployment
wired into the actual workflow.
Adoption tracked
real people using it, numbers to show it.
ROI reported monthly
baseline vs now, in currency.
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