AI MVP DEVELOPMENT / UNITED KINGDOM
Prove the AI product before you scale it.
AI MVP development for UK startups and product teams: a focused first release of an AI product, with an evaluation set, running-cost visibility and a plan to grow from evidence.
UK-registered company. International engineering team.01 / THE OPPORTUNITY
AI MVP development for UK businesses.
An AI product idea is easy to demo and hard to ship. The gap is filled by unglamorous work: representative examples, an evaluation set, a cost model, permissions, a fallback when the model is unsure. Krapton builds AI MVPs for UK founders that close that gap early, so the first release is something real users can rely on.
We scope the MVP around the assumption you most need to test, build it on proven components (models from OpenAI, Anthropic or Google, retrieval over your data, a Next.js or mobile front end), and instrument it so the next decision is made on usage rather than hope.
02 / Use cases
AI assistant products
A vertical assistant for a profession or task, grounded in curated knowledge and priced per seat or per use.
Document understanding
Extract, classify and summarise contracts, forms or reports for a specific industry.
Workflow copilots
Draft, check and route routine work inside an existing process, with a human confirming the result.
AI search and discovery
Natural-language search over a catalogue, archive or knowledge base with cited answers.
03 / Our approach
Evaluation before release, guardrails by design and people in control of the decisions that matter.
AI development overview- 01
Discovery sprint
The user, the task, the riskiest assumption and the examples that define a good result. A prioritised scope and a fixed quote.
- 02
Evaluation set first
A test set built from real examples, so every prompt, model or data change can be measured before users see it.
- 03
Build the thin product
The core journey, onboarding, billing where needed and the AI feature, shipped in short cycles with weekly demos.
- 04
Launch and learn
Usage, quality and cost dashboards from day one, then a roadmap decided by evidence.
04 / Before you start
The decisions that shape the build.
Model running costs scale with usage, so pricing and rate limits are designed with the product. Personal data in prompts and outputs falls under UK GDPR; we agree data flows and retention with you before launch.
What every AI engagement includes
- A use case with a measurable result and representative examples
- An evaluation set rerun on every prompt, model or data change
- UK GDPR-aware data flows, with UK or EU hosting where residency matters
- Human review and defined permissions for anything consequential
- Cost and quality monitoring after launch
05 / From the portfolio
Examples from Krapton’s international portfolio. Each success story describes the work delivered for that project.
Dental.AI
Dental.AI set out to give patients instant, AI-driven insight into their oral health from a single dental image — which meant pairing a clinical-grade analysis pipeline with a web experience patients actually trust.
Read the success storyFAQ
It depends on the platform, the data work involved and the integrations. A grounded assistant over a curated knowledge base is a smaller project than an agent that acts in several systems. We quote a fixed scope in GBP after discovery; the cost calculator gives an indicative range first.
A focused AI MVP typically launches within a few months of discovery. Data readiness and the evaluation work are the main variables, so we start them in week one.
The one that performs best on your evaluation set at an acceptable cost and latency. We compare models from OpenAI, Anthropic and Google, and open-weight options where private hosting matters, and recommend on evidence.
By measuring cost per request from the first prototype, caching and retrieval strategies that reduce tokens, model routing for simple versus complex tasks, and product limits that match your pricing.
Yes, if it is built properly. We use an architecture and code quality that lets the MVP grow, rather than a throwaway prototype that has to be rebuilt after fundraising.
Related
MVP development
A focused first product to validate demand with real UK users.
ExploreAI development
Assistants, agents, RAG search and automation built on your data.
ExploreApplication development
Web and business applications with clear workflows and room to grow.
ExploreHealthcare AI development
Clinical admin, triage and patient tools built with governance in mind.
ExploreFintech AI development
Onboarding, risk and support automation for regulated finance.
ExploreLegal AI development
Contract review, document drafting and client intake for law firms.
Explore
YOUR NEXT STEP
Bring the task, the examples and the systems involved. We’ll tell you what an evaluation set, a prototype and a first release would look like.