Fits your architecture
We work inside your codebase, conventions and deployment pipeline alongside your engineers.
AI Integration
Bring AI into the product you already have.
We embed AI features into existing products and internal platforms — smart search, summarisation, classification, recommendations and copilots — without rebuilding what already works.
AI Integration
We don't stop at a demo. Every AI Integration engagement ships to production with evaluations, monitoring and documentation — measured against the outcomes that matter to your business.
Outcomes
What this means for your business
Cost and latency under control
Model selection, caching and prompt design tuned for speed and predictable spend.
Ship incrementally
Features launch behind flags and are measured, so every release proves its value.
What's included
Typical deliverables — tailored to your scope in our proposal.
- Technical assessment
- Model and vendor selection
- API and backend integration
- Front-end AI features
- Cost and performance optimisation
- Monitoring and evaluations
Example use cases
Common projects our clients start with.
Semantic searchSummaries and smart draftsClassification and taggingRecommendationsIn-app copilotsSpeech and transcription
Typical technology
Chosen per project based on your requirements.
OpenAIAnthropic ClaudeAWS BedrockAzure OpenAINode.jsPython
How we deliver
From kickoff to launch
Discover
1–2 weeksWe map your goals, users, data and constraints, then define the highest-value use case and how success will be measured.
Prototype
1–3 weeksA working prototype tests the riskiest assumptions with real data — so you see results before committing to a full build.
Build
4–10 weeksWe engineer the production solution in short sprints with weekly demos, evaluations and full transparency on progress.
Launch & scale
OngoingWe deploy, monitor quality and cost, and keep improving — or hand over to your team with documentation and training.
How long does it take to build an AI MVP?
Most MVPs take six to twelve weeks, depending on scope, integrations and data readiness. We agree milestones up front so timelines stay predictable.
Who owns the code and IP?
You do. All code, prompts, models, documentation and intellectual property created for your project are transferred to you.
How do you handle data privacy and security?
We follow least-privilege access, keep your data in your environment wherever possible, sign NDAs and DPAs on request, and use model providers configured not to train on your data.
How is pricing structured?
Discovery Sprints and MVP builds are fixed-price against an agreed scope. Dedicated teams are billed monthly. You'll receive a detailed proposal after our first call.
Related services
Often combined with
Let's talk about your AI Integration project.
Tell us what you're working on. We'll reply within one business day with honest advice on the fastest path to results.