GENERATIVE AI DEVELOPMENT / UNITED KINGDOM
Generative AI features that ship inside real products.
Generative AI development for UK businesses: text, image and code generation features built into your products and workflows, with brand controls, review steps and cost management.
UK-registered company. International engineering team.01 / THE OPPORTUNITY
Generative AI development for UK businesses.
Generative AI is most valuable when it is a feature inside something people already use: a proposal drafted inside the CRM, product imagery generated inside the catalogue tool, code suggestions inside the developer workflow, personalised messages inside the marketing platform. Krapton builds those features for UK businesses, with the controls that make them safe to put in front of customers and staff.
We handle prompt and context design, brand and tone controls, review and approval steps, output validation, cost management and the evaluation that shows whether the feature is good enough. The models come from OpenAI, Anthropic, Google or open-weight providers, chosen on evidence.
02 / Use cases
Content and copy generation
Proposals, product descriptions, campaign variants and summaries in your voice, reviewed before publication.
Image and media generation
Product visuals, variations and creative assets generated within brand guidelines.
Code and configuration generation
Assistants that generate code, queries or configuration for your internal tools and platforms.
Personalisation at scale
Messages, recommendations and experiences tailored per customer from first-party data.
03 / Our approach
Evaluation before release, guardrails by design and people in control of the decisions that matter.
AI development overview- 01
Feature definition
Where the feature lives, who uses it, what good output looks like and what must never be generated.
- 02
Prompt, context and controls
Structured prompts, retrieval of brand and product context, output validation and tone controls.
- 03
Evaluate and refine
Human ratings and automatic checks on a sample set, iterated until quality is consistent.
- 04
Ship with review and cost limits
Approval steps where needed, usage limits matched to pricing and monitoring of quality and spend.
04 / Before you start
The decisions that shape the build.
Generated content can reproduce bias, inaccuracies or third-party material, so review steps and provenance records matter, especially for regulated sectors and consumer communications. Intellectual property terms for generated media are checked for the models used.
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
Text models from OpenAI, Anthropic and Google, image models where the licence suits commercial use, and open-weight models where private hosting is preferred. We choose on evaluation results for your use case.
Yes. Tone guides, examples and retrieval of your existing content shape the output, and a review step keeps a person in charge of what is published.
Ownership depends on the model provider’s terms and UK law, which is still developing in this area. We use providers whose commercial terms are clear and document them for your legal review.
Model routing, caching, prompt efficiency and usage limits designed with the product, and monitoring of spend per feature and per customer.
Yes. A private assistant grounded in your data, deployed within your Microsoft 365, Google Workspace or web environment, with permissions and audit logging, is a common engagement.
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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.