AI Integration
Practical AI features such as document search, assistants and forecasting, connected to your own data.
Practical AI that solves real business problems
AI is most useful when it is connected to your own data and workflows. We build AI features that save time and improve customer experience, such as chat assistants that answer from your content, search across your documents and automation of repetitive work, with the guardrails a business needs.
For example, we built an AI booking assistant for a medical clinic that lists specialties, finds doctors, shows schedules and books appointments in chat. You can read about it in our portfolio.
What we build
- AI chatbots and assistants for websites, apps and WhatsApp-style messaging
- Document search and question answering over your files (RAG)
- Extraction of data from invoices, forms and emails
- Classification, routing and summarisation of tickets and messages
- Forecasting and anomaly detection on business data
- AI features added to your existing web or mobile app
Models and tools
We work with leading model providers such as Anthropic Claude and OpenAI, and with open models that can run on your own servers when data must stay in-house. Retrieval uses vector search (for example pgvector), and every feature is evaluated against real examples before it goes live.
Safe and reliable by design
- Your data is not used to train public models
- Answers are grounded in your own content, with limits on what the assistant may say
- Sensitive data can stay in a private deployment
- Monitoring of quality and cost after launch
Start small
Most clients begin with a focused pilot on one use case. If it proves its value, we extend it to more workflows.
AI Integration: common questions
Our work
See what we have built for clients in our portfolio.