Is your AI idea worth building?
Test it in just three weeks with a working proof of concept —and know if it works, adds value, and deserves investment.
Reserve a slotThe sprint
Define, build and validate. You keep the PoC.
Experiencing any of these?
“Add AI” but the direction and value are unclear
Leadership wants AI in the product, but without clear guidance on what to build, why it matters, or what business value it should create.
“This could be solved with AI… maybe?”
You suspect AI could help solve a problem, but don’t know if it’s feasible, realistic, or even the right approach.
Too vague to become a Business Case
AI comes up in stakeholder discussions, but the ideas lack the clarity needed to be evaluated or funded.
AI ideas stuck in your head
You see opportunities for how AI could improve your product, but struggle to turn them into a roadmap item or backlog initiative.
AI feels like a black box
There’s an AI initiative or team in the company, but from a product perspective it’s unclear what to build or prioritize.
The neighbor FOMO effect
You’re not ready to take on a high-cost, high-risk AI bet, but competitors are launching AI features and the pressure is hard to ignore.
Have you been here or there with AI?
We’ve seen teams get stuck at both extremes of the AI spectrum. We built the middle ground.
Doing nothing feels safer
You might delay action because starting with AI seems to require:
Big upfront costs and long-term commitments
Pulling focus away from your core product
Slow executive approvals that demand certainty you don’t yet have
While you’re weighing the ‘ifs,’ your competitors are shipping the ‘hows.’ This paralysis isn’t a lack of vision—it’s because every idea feels too expensive to explore.
Going “all in” feels like a bet
There’s a high risk in committing before you know:
If the problem is worth solving
If AI is the right approach, and if the idea is feasible
If customers care, and if the value is real
If you’re pouring resources into an AI idea you haven’t tested, the prediction is resource waste. 85% of AI projects fail because they skip the experiment and jump straight to the commitment.
You don’t have to wait, and you don’t have to bet big
There’s a path in the middle. A PoC is a small, focused experiment to test whether an AI idea is feasible and valuable before serious investment.
Test one real use case
Without long-term commitments
Learn in weeks, not months
While changes are still cheap
Decide with evidence
Not slides or vendor promises
Stop early when needed
Saving time, money, and credibility
AI concept validation sprint
A way to dip your toe in the water with AI without locking yourself into a long-term bet.
What it is
A test of feasibility, business relevance, and usability
A working proof of concept, tailored to your context
An experiment to decide whether your AI idea is worth pursuing
What it is not
A production system or MVP
Market or problem discovery
A roadmap, estimates, or delivery plan
What you’ll have at the end
Tangible outputs that make the abstract feel concrete.
Functional Mini-App (POC)
A working proof that demonstrates real AI behavior.
Demo Recording
A walkthrough video you can share with stakeholders.
Executive Summary
A concise document outlining findings, constraints, trade-offs, and key learnings.
Next-Steps Recommendation
Clear options for what to do next, whether to proceed, iterate, or stop with confidence.
How we get there in three weeks
A transparent process that takes little of your time and delivers profound learnings and recommendations.
Week 1 · Define the Concept
Week 2 · Build the PoC
Week 3 · Validate the Proof