AI that actually works in production.
LLM pipelines, RAG systems, AI agents, vector databases — we build production-grade AI features that deliver real value, not just demos.
Key capabilities
The right AI provider for you
OpenAI ChatGPT, Anthropic Claude, Google Gemini or open-source alternatives — we help you choose the provider that fits your needs, budget and data privacy requirements, then integrate it properly.
AI that knows your data (RAG)
We connect the AI to your own documents, databases and knowledge base so it answers questions based on your real information — accurately and with sources, not guesses.
AI agents that get things done
AI that does not just answer — it acts. Agents can search the web, query databases, fill forms, call other services and complete multi-step tasks from start to finish on your behalf.
Connected to your tools
We give the AI access to the tools it needs — your CRM, calendar, databases, APIs — so it can take real actions in your systems, not just generate text.
Quality you can trust
We build monitoring and evaluation into every AI integration so you always know how well it is performing, catch problems early and can improve it over time with confidence.
Trained on your business
When a general AI provider is not precise enough, we fine-tune it on your data so it speaks your language, knows your products and performs at the level your business needs.
Our process
Find the Right Opportunity
We look at your business and identify where AI will genuinely save time, improve quality or open new possibilities — not where it sounds impressive but adds no real value.
Prepare Your Data
For the AI to be useful, it needs to understand your world. We organise, clean and connect your documents and data so the AI has what it needs to perform well.
Choose the Provider & Build
We select the best AI provider for your use case, build the integration and test it rigorously against real scenarios until the quality meets your standards.
Launch & Keep Improving
We deploy to production, monitor performance from day one and keep optimising — because a good AI integration gets better with time, not worse.
Our stack
Use cases
Smart Search
Your users type a question in plain language and get exactly what they are looking for — from your product catalogue, knowledge base or internal documents — instantly.
Ask Your Documents
Upload your contracts, manuals or reports and ask questions in plain language. The AI reads them and answers accurately, pointing to the exact source.
AI Assistant Inside Your Product
An AI assistant that lives inside your app and knows your business — helping your users get things done faster without needing to contact your support team.
Automated Content & Drafts
AI that drafts product descriptions, email replies, reports or support responses in your brand voice — ready for a human to review and publish in seconds.
FAQ
Which AI provider should we use?
It depends on your needs. OpenAI ChatGPT, Anthropic Claude and Google Gemini all have different strengths in terms of reasoning, cost, speed and data privacy. We help you compare them honestly and choose the right fit — or combine more than one.
Will the AI make things up or give wrong answers?
This is a real risk with AI, and we take it seriously. By connecting the AI to your own data using RAG, and adding source citations and human review steps, we keep answers grounded and trustworthy.
Is our data safe with third-party AI providers?
We make sure of it. We review each provider's data policies, configure API settings so your data is never used to train their models, and can deploy open-source models on your own infrastructure if full privacy is required.
How much will it cost to run AI in production?
It depends on how much you use it, but we design integrations to be efficient — caching repeated requests, routing simple queries to cheaper providers and setting spending limits so there are no surprises on your bill.
How quickly can we have something working?
A first working version typically takes 2–4 weeks. A fully production-ready integration with monitoring and quality controls usually takes 6–12 weeks, depending on the complexity and how ready your data is.
Ready to add real AI to your business?
Tell us what you want the AI to do and we'll find the right way to make it happen — with the provider that fits you best, built to actually work in production.
Start your project