AI proofs of concept and product MVPs when the model path is still uncertain
A hands-on PoC to prove the AI task is solvable, then an optional product MVP around it. Choose this when the model or data path is the risk, not when you already have a scoped use case (that is the AI Pilot) or a non-AI product idea (MVP Development).
Does this sound like your team?
“Investors or customers want to see AI working, not a mock-up”
“You are not sure whether to build a PoC or go straight to MVP”
“Past demos never made it past the meeting”
What you get with AI PoC & MVP Development
- PoC scope and success criteria
- Working PoC on real or representative data
- PoC vs MVP recommendation
- MVP build: auth, UI, data, billing if needed
- Evaluation results and cost per run
- Production architecture plan
PoC vs MVP vs Pilot Decision Tree
One page that answers what you should build first when the AI path is still uncertain.
Phases, timelines and what you receive
Discover
Use-case scope, KPI baseline, data access plan
Pilot
Working pilot on real data with evaluation results
Production
Hardened, integrated, monitored system
Improve
KPI and cost reports, new use cases shipped
What we measure before Go / Adjust / Stop
Every phase ends with a decision based on numbers agreed at the start.
Quality
accuracy against a labelled test set agreed up front
Speed
response time your users will accept
Cost per run
model and infrastructure cost per task
Edge cases
what happens with bad input, silence or unknown requests
Get a plan for AI PoC & MVP Development
A few fields, no sales script. We reply within 1 business day with next steps.
Where we've done this before

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AI recruiting that sources, matches and ranks candidates against each job's real requirements

Agent ops from prototype to production
An operations console to register, run, monitor and govern fleets of AI agents
Senior people, named roles
Lead AI Engineer
Owns architecture, model choice and evaluation.
Full-stack Engineer
Builds integrations, UI and data pipelines.
Product Designer (on demand)
For user-facing assistants and dashboards.
What we build with
Industries we deliver this for
Start small, with a clear decision point
Most AI work starts with a workshop or a 4-6 week pilot.
Who this is not for, and what we won't do
- We don't build MVPs before the PoC proves the core AI works
- We don't hide model costs until after launch
What clients say
Frequently asked questions
Straight answers on cost, timelines, ownership and data.
A PoC proves the AI can do the task (4-6 weeks). An MVP wraps it in a product real users can use (6-10 weeks after). If the AI part is uncertain, start with the PoC.
It depends on features and integrations. Every PoC or MVP gets a written quote after a short scoping call.
Yes. See Application Modernization.
Ready to talk about AI PoC & MVP Development?
Book a short call with a senior engineer. No pitch deck, just a clear next step.
- We reply within 1 business day.
- NDA available on request
- You own all code from day one








