Applied AI for product teams — from first prototype to production
We build LLM integrations, agent systems and data pipelines that hold up outside of a demo environment. Typically engaged by engineering teams and founders who need to move fast without building on shaky foundations.
Talk to us about your AI project →Our AI & Machine Learning services
LLM Integration
Connecting large language models (GPT-4, Claude, Gemini) to existing products and workflows. Covers API integration, prompt design, context management, fine-tuning and cost control.
AI Agents & Workflows
Multi-step agentic systems that can reason, plan and execute across tools and data sources. We have used LangChain and LangGraph in production.
RAG Systems
Retrieval-augmented generation systems that ground model outputs in your own data. Covers embedding pipelines, vector stores and retrieval tuning.
AI Prototyping & Validation
A short, fixed-scope engagement to test whether an AI approach is viable before committing budget to a full build. Typically 2–4 weeks.
What working with us looks like
We understand the problem, the data, and what good looks like before writing any code. We'll tell you honestly if AI isn't the right approach.
We test the core technical approach against real data with a working prototype before committing to a full build.
Built in defined, testable phases with regular client reviews. We write for maintainability — your team needs to own this after we leave.
Documentation, knowledge transfer and a defined handover period. A clear handover, not a dependency on us.
FAQ
Does my project actually need AI, or would a simpler approach work?
How do you evaluate whether an AI approach is viable?
Can you work with our existing data?
How do you measure whether an AI feature is working in production?
What happens after the engagement ends?
Ready to build something?
Tell us about your project and we'll come back to you within 24 hours.
Let's Talk →