PoC Development Services
Prove the riskiest assumption before you fund the build: 2-4 week sprints with a working demo and a written go/no-go.
Companies we've collaborated with
Prove the Risky Part Before You Fund the Build
What is PoC development?
Proof-of-concept development is a short, fixed-scope sprint that proves (or disproves) the riskiest assumption in your product idea before you commit real budget. You get a working technical demonstration, a written go/no-go recommendation, and an honest estimate of what production would take. Two to four weeks.
What a PoC Engagement Includes
PoC Sprint
Two to four weeks against the one assumption that could sink the idea: a working demonstration, not slides. Fixed scope, agreed before work starts.
Go/No-Go Report
A written recommendation you can act on with us or anyone else: what we proved, what we couldn’t, what production would honestly take. Some reports say don’t build. That’s the cheapest outcome we sell.
MVP Build
When the answer is go and the question becomes demand, we build the v1 that tests it. Usually six to ten weeks.
AI Pilot Routing
If your “PoC” involves language models doing real work, it’s usually an AI pilot: evaluation and a production track from day one, on our AI consulting ladder. We’ll tell you which one you’re describing at the first call. Runs on the AI consulting ladder.
What you get, fixed scope
A proof of concept exists to answer a question, not to ship. That changes how the code gets written: fast, focused on the risky part, and disposable if the answer is no.
PoC, pilot, or MVP: which one do you need?
These three get used interchangeably and they should not be. Pick the one that matches the question you actually need answered, and we will tell you at the first call if you have described a different one.
PoC Sprint
Proves feasibility. Can this be built at all?
- Two to four weeks, fixed scope
- One riskiest assumption, tested for real
- Working demo plus written go/no-go
- Throwaway code acceptable by design
AI Pilot
What most people mean by an "AI PoC".
- For language models doing real work
- Evaluation against real data from day one
- Production track scoped up front
- Runs on the AI consulting ladder
MVP Build
Proves a business. Do people want it?
- Six to ten weeks to a real v1
- Scoped to the smallest thing that tests demand
- In front of real users, not stakeholders
- Same philosophy as our mobile development work
Two to four weeks, start to answer
Pin the assumption
Week one. We agree on the one thing worth testing and strip everything else out of scope, in writing.
Build the demonstration
Weeks two and three. We check in as we go. No silence followed by a reveal.
Deliver the answer
Final week. Working demo, go/no-go recommendation, and productionizing estimate, all in writing.
Take it anywhere
The document stands alone. Build it with us, with your team, or not at all.
Is your question a PoC question?
Worth a PoC
- Can the vendor API actually return data at the speed the sales deck claims?
- Will the recognition model hold up on your real images, not the demo set?
- Can the legacy system be integrated without a rewrite?
- Does the hard interaction feel right in a user’s hands?
Not a PoC
- “Will people pay for this?” That is market validation, and software is a slow way to answer it.
- Boring, proven technology. A standard integration or conventional web app needs a scoped v1, not a feasibility test.
- A question you can answer with a phone call to the vendor.
Three things, and none of them are engineering
PoCs die from vague goals and slow answers, not hard problems. The fixed scope protects you from us; the weekly check-in protects the sprint from drift.
We ran this play on ourselves
CodeRaven, our AI code-review platform, started exactly this way. The risky assumption was that a language model could review production pull requests with enough signal that engineers would not ignore it, at a cost that made always-on review rational. We tested it against our own repositories before building any product around it.
days of production history
approval rate from the engineers merging the code
total model spend across the period
What goes wrong with proof-of-concept work
Three failure modes cover most PoC disasters. Each one is handled by how the sprint is structured, not by hoping.
Scope creep
The demo grows features nobody agreed to and four weeks becomes twelve. Prevented contractually by the fixed scope, and culturally by writing down what we are not building.
Proving the wrong thing
The demo works, but it tested the easy path instead of the risky one. That is why week one is spent pinning the assumption before any code is written.
The quiet fake
A demo that looks like it works because it is wired to happy-path data. We have catalogued what convincing facades look like, and the report states exactly what was exercised for real.
Why run a PoC with SLIDEFACTORY?
Because our founders have been on both sides of this decision across more than 25 years of shipping software, and we build our own products too. CodeRaven, our AI code-review platform, started as exactly this kind of scoped bet before it became a product with 148 days of production history. Client work follows the same pattern: a VR training program that began as a three-month initial build and grew into a five-year engagement, and a recommendation engine that shipped inside a national client’s product. Scoped first bets, expanded when they earned it. If your build involves web and mobile applications, that’s our home turf.
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Frequently Asked Questions
How much do PoC development services cost?
Each sprint is priced when it is scoped, because the risky assumption is different on every project. PoC sprints run two to four weeks and MVP builds usually six to ten. Both are fixed-scope: the number and the calendar are agreed before work begins.
Do we keep the code?
Yes, everything we write is yours. But PoC code is built to answer a question, not to ship, and we’re explicit about that. The go/no-go report tells you which pieces are production-worthy and which should be rewritten if you proceed.
What happens if the PoC fails?
Then it worked. A proof of concept that disproves the idea for four figures has saved you a six-figure build. You still get the full written analysis: what broke, whether a different approach could work, and what we’d try instead.
What's the difference between a PoC and an MVP?
A PoC proves the thing can be built; an MVP proves people want it. If nobody has demonstrated technical feasibility, start with the PoC. If the technology is known and the question is demand, skip straight to a scoped v1.
Can you do a PoC for an AI product?
Yes, but we’ll be honest about what it is. AI features need evaluation against real data from day one, so “AI PoC” work usually runs as a fixed-scope pilot on our AI consulting ladder instead. Same idea, right tooling.
