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AI Modernisation
Add AI to what
you already have.
You don't need to start over. We integrate AI capabilities into your existing product — intelligently, incrementally, and without disrupting what's already working.
What we deliver
- AI feature layer on top of existing codebases
- LLM integration — OpenAI, Anthropic, Gemini, open-source
- Semantic search and RAG over existing data
- AI-assisted UX — autofill, suggestions, summaries
- Legacy API modernisation with AI middleware
- No full rewrite — incremental, production-safe delivery
Ways teams add AI to a live product
An assistant over existing data
A conversational surface on the product your users already know.
Automating a manual step
Take the one workflow your team complains about and remove the typing.
Migration and upgrade work
Modernise the stack far enough that adding AI is not fighting the codebase.
Related reading
FAQ
Frequently asked questions
- Can you add AI without rewriting our application?
- Usually yes. Most AI features attach at the edges — a new service, a new surface, an integration — rather than requiring changes to core business logic. We start by finding the seam that needs the least disruption.
- Our codebase is old. Is that a blocker?
- Rarely a blocker, sometimes a cost. If the architecture makes integration expensive, we will say which parts need modernising first and why, rather than quietly padding the estimate.
- How do we know the AI feature is worth keeping?
- Instrument it from day one. Usage and measured quality decide whether it expands or gets removed — that is cheaper than arguing about it.
- What about our compliance obligations?
- Retrofitting AI touches retention, consent and erasure in ways teams often miss, particularly around prompt logs and vector stores. Our DPDP Act post covers what actually has to change.
- Can you work alongside our in-house developers?
- Yes, and it is often the best structure — your team knows the domain, we bring the AI engineering, with clear interfaces between the two.