AI Solutions
Generative AI Integration
Add useful AI features to the website, SaaS product or mobile app you already have. We handle model choice, retrieval, testing and cost, so your users get answers they can trust.
AI inside the product your users know
You do not need a new platform to offer AI. Most of the value comes from placing a few well-chosen features where users already work: a search box that understands questions, a summary at the top of a long record, a suggestion at the right moment.
We work with your existing codebase and team, add the AI layer through clean APIs and keep it measurable, so you can see what each feature costs and how often it helps.
Features we add
Semantic search
Search that finds results by meaning, so users get the right product, article or record even when their words differ from yours.
RAG over company knowledge
Answers drawn from your documents, help center or database, with citations, permissions respected and content kept up to date.
Summarisation
Short summaries of long documents, tickets, calls and records, so users get the point in seconds.
Recommendations
Suggestions for products, content or next steps based on behaviour and item similarity, explained in plain words.
AI features in SaaS and mobile
Drafting, classification, smart forms and natural-language filters built into your web or mobile app.
Evaluation and guardrails
Test sets, automatic scoring, content filters and limits that keep output accurate, safe and on brand.
Model selection and cost control
No single model is best at everything. We compare OpenAI, Claude, Gemini and open-source options on your own tasks for quality, speed and price, and often route simple requests to smaller, cheaper models.
Caching, prompt design and usage limits keep monthly costs predictable. We build behind a thin model layer, so you can switch providers later without rewriting your product.
How we deliver an integration
Built alongside your product team, released behind feature flags.
01 / 05
Pick the feature
We review your product and user data, shortlist AI features by value and effort, and agree how each will be measured.
Technology
OpenAI, Claude, Gemini
- Hosted APIs with enterprise terms
Open-source models
- Self-hosted or private cloud
Vector databases
- pgvector, Qdrant, Pinecone
- Hybrid keyword and semantic search
Python
- Retrieval pipelines and evaluation
.NET and Node.js
- Product APIs and backend services
React, Next.js, Flutter
- AI features in web and mobile interfaces
Frequently asked questions
Still have questions?
Talk to a business developer directly. We usually reply within an hour during working hours.
Retrieval-augmented generation means the model looks up your own content before it answers. You need it whenever answers must be based on your documents or data rather than general knowledge.
Add AI to your product
Tell us about your product and users. We will suggest the AI features most likely to help and estimate their build and running costs.