Proof of concept or MVP?
The two answer different questions, and we help you pick the right starting point.
Proof of concept
A focused build that answers one question: does this work? It proves the AI approach is feasible with your data and your problem, quickly and at low cost, so you learn before you invest.
Minimum viable product
A small but real product that users can actually use. It tests whether the thing people will adopt and pay for, not just whether the technology functions, and gives you something to take to a board, an investor or a first cohort of users.
Built to prove value, then to scale
We build deliberately, so a successful proof of concept has somewhere to go. That means sensible architecture, your data handled properly, and a clear line from prototype to production rather than a throwaway demo you have to rebuild. When a build works, you can extend it. When it does not, you have learned that cheaply, which is just as valuable.
Where this works well
Regulated and high-stakes environments
We are used to building where data sensitivity, security and governance matter, so AI is introduced responsibly rather than recklessly.
Businesses new to AI
If you want to move beyond experimenting with chatbots to something that solves a real operational problem, a proof of concept is the low-risk way in.
Investment and board conversations
A working MVP is far more persuasive than a roadmap. It shows a board or an investor that the idea is real and that you can execute.
How an engagement runs
We start by defining the problem and the single question the build needs to answer, then scope a fixed, time-boxed piece of work. We build, we test it against that question, and we hand you a clear read on the result with a recommendation on what to do next. Short, defined, and honest about the outcome.
Practical and grounded, not hype
We are not here to sell AI for its own sake. Some problems do not need it, and we will tell you when that is the case. The value is in solving the actual problem, sometimes with AI, sometimes with something simpler, and always with a clear-eyed view of cost, risk and return.
Work with Keekco
Book a call to scope an AI proof of concept, or take the two-minute readiness check to see where you stand with AI today.
Frequently asked questions
- What is an AI proof of concept?
- An AI proof of concept is a focused, low-cost build that answers one question: does this AI approach work for your problem and your data? It lets you learn whether an idea is feasible before committing to a full product.
- What is the difference between a proof of concept and an MVP?
- A proof of concept tests whether the technology works. A minimum viable product is a small but real product that tests whether people will use and value it. A proof of concept often comes first; a successful one can grow into an MVP.
- How much does an AI proof of concept cost?
- It depends on the problem and the data involved, but a proof of concept is deliberately small and time-boxed to keep cost and risk low. We scope a fixed piece of work so you know the cost before you start.
- How long does it take?
- Proofs of concept are short by design, typically a matter of weeks rather than months, because the point is to learn quickly before investing further.
- Will the proof of concept be reusable if it works?
- We build with that in mind. A successful proof of concept is designed so it can be extended toward production rather than thrown away and rebuilt.
- What if AI is not the right answer?
- We will tell you. Some problems are better solved without AI, and we would rather save you the spend than build something that does not earn its place.