AI Development Grounded in a Real Business Problem
From an LLM-powered feature inside an existing product to a new AI-driven workflow — scoped around a problem worth solving, not a technology looking for a use case.
Scope, timeline, and cost agreed in writing before development starts.
Who This Is For
- Businesses that want to add AI features to an existing product
- Startups building an AI-native product from the ground up
- Teams that need help scoping what AI can realistically do for them
The Problem
"Add AI" is not a scope. Many AI initiatives stall because the problem the AI is meant to solve was never clearly defined, or because the approach chosen doesn't match the data and constraints actually available.
Our Approach
We start by identifying a specific, testable problem AI can address for your business, then build and integrate the smallest version that proves it — before scaling up.
What's Included
- LLM-powered feature design and integration
- Retrieval-augmented generation (RAG) systems
- AI workflow and automation design
- Model evaluation and prompt engineering
- Integration with existing product and data infrastructure
- AI feature scoping and feasibility assessment
What You Get
- A clearly scoped AI feature tied to a specific business problem
- A working integration inside your existing product or a new one
- An honest read on where AI is (and isn't) the right tool before you spend on the wrong approach
Our AI Development Process
- 01
Discovery
A working session to understand your goals, constraints, users, and what success looks like.
- 02
Scope & Proposal
A written proposal covering scope, approach, timeline, and cost before any code is written.
- 03
Design & Architecture
Technical architecture and, where relevant, UI design, reviewed with you before build starts.
- 04
Build
Iterative development with regular check-ins, so you see progress rather than a black box.
- 05
Launch & Support
Deployment, handover, and an agreed support arrangement for the period after launch.
Technologies We Work With
AI Development FAQs
We don't know exactly what we want AI to do yet — can you help scope it?
Yes, that's typically the first part of the engagement, before any build commitment.
Do you build our own models or use existing LLM APIs?
Most business problems are best solved with existing LLM APIs plus good retrieval/integration work. We'll recommend that honestly rather than defaulting to a bigger build than the problem needs.
How do you handle our data?
Data handling and any third-party model providers used are agreed with you explicitly before implementation.
Ready to Talk About Your AI Development Project?
Tell us what you're trying to build. We'll respond with next steps, not a sales pitch.