AI & Generative AI
AI applications that do real work for your business.
We design and build AI products and features, from assistants and agents to document processing and AI search, on the model that fits each job and connected to the data and systems you already use.
AI Development
AI applications, assistants, agents and RAG systems built on Claude, OpenAI and Gemini, and connected to your data.
Technology
- Claude
- OpenAI
- Gemini
- RAG
- Vector databases
- Next.js
The challenge
Why most AI projects stall
Demos that don't reach production
A prototype that impresses in a meeting often breaks on real data, real users and real edge cases.
AI that knows nothing about your business
Generic models give generic answers unless they are grounded in your documents, products and policies.
Isolated from your systems
An assistant that can't read your CRM or update an order creates more manual work, not less.
Our approach
Production AI, engineered properly
We treat AI as software engineering. That means a clear use case, the right model, retrieval over your own data, integrations with your tools, evaluation against real examples, and monitoring once it's live.
- Use-case discovery and feasibility before build
- Model selection across Claude, OpenAI and Gemini
- Retrieval-augmented generation (RAG) on your content
- Evaluation sets, guardrails and human-in-the-loop review
How an AI system connects
- User
- Interface
- AI agent
- Knowledge (RAG)
- Your systems
- Action
- Review & logs
What we deliver
AI development services
AI application development
Standalone AI products and AI features inside your existing web or mobile apps.
AI assistants & chatbots
Customer-facing and internal assistants that answer from your knowledge base.
AI agents
Agents that plan and take actions through tools: CRM, database, email, WhatsApp and APIs.
RAG & knowledge bases
Search and answer over documents, policies, product catalogues and tickets.
AI search & recommendations
Semantic search and personalised recommendations for content and products.
Document processing
Extract, classify and validate data from invoices, contracts, forms and IDs.
AI data analysis & reporting
Natural-language questions over your data, with automated summaries and reports.
AI SaaS
Multi-tenant AI products with billing, usage limits and admin controls.
Multi-model architecture
Model routing and fallbacks so each task uses the best model for cost and quality.
Prompt & workflow engineering
Prompts, tools and workflows designed, versioned and tested like code.
Use cases
Where AI pays off
Customer support
Answer common questions instantly from your policies and order data, and hand over to a person when needed.
Sales enablement
Qualify leads, draft proposals and summarise calls so your team spends time on closing.
Operations
Read incoming documents, extract the data and push it into your ERP or accounting system.
Internal knowledge
Give staff one place to ask questions across manuals, SOPs and past projects.
Technology
- Claude
- OpenAI
- Gemini
- RAG
- Vector databases
- Next.js
- Python
- Node.js
- PostgreSQL
How we work
A clear process from idea to growth.
Eight stages, with visible progress and a working product early.
Discover
We understand your business, users, goals and constraints before proposing anything.
Plan
Product and technical strategy: scope, architecture, milestones and a clear estimate.
Design
User journeys, UX and UI designed around how your customers actually behave.
Build
Iterative development in short cycles, with working software you can review early.
Integrate
Payments, APIs, AI models, CRMs and automation connected into one system.
Test
Functional QA, security checks, accessibility and performance testing.
Deploy
Production deployment with CI/CD, monitoring and a documented rollback path.
Grow
Ongoing optimisation, maintenance, automation and support after launch.
Why it matters
What you gain
Faster responses
Customers and staff get answers in seconds rather than hours.
Lower operating cost
Repetitive reading, typing and searching is handled by AI.
Better decisions
Data and documents become searchable and easy to summarise.
No vendor lock-in
A model-agnostic architecture lets you switch providers as the market moves.
Frequently asked questions
AI Development
Which AI model should we use?
It depends on the task. We compare Claude, OpenAI and Gemini models on your real examples for quality, speed, cost and data requirements, and often combine models within one product.
Is our data used to train public models?
We use provider APIs and configurations that don't use your API data for model training by default, and we design data flows so only what's necessary is sent to the model. We confirm the specifics per provider during planning.
How long does an AI project take?
A focused proof of value typically takes a few weeks. Production systems with integrations, evaluation and monitoring take longer. We scope this during discovery.
Can AI be added to our existing application?
Yes. Many projects add AI features such as search, summaries, assistants or automation to an existing website, app or internal tool.
Quick quote
Get a quote for AI Development
Tell us a little about what you need. We'll reply with next steps, a rough timeline and a cost range. No obligation.
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Have an AI idea or a process to improve?
Tell us the use case. We'll tell you what's feasible and how we'd build it.