AI Integration

We build software that puts large language models to practical use. That means applications that automate knowledge work, process documents at scale, answer questions across large volumes of content and generate outputs that previously required a human expert.

What we build

RAG systems

Retrieval-augmented generation over internal documents, wikis or databases. Ask questions in plain English and get accurate, sourced answers.

Document processing

Extract, classify and structure information from unstructured documents at scale. Forms, reports, contracts, correspondence and more.

Report generation

LLM-powered pipelines that turn raw data or analysis into readable, well-structured documents and summaries.

AI agents

Systems that reason through multi-step tasks using tools and APIs. Useful for automating research, data gathering and decision support workflows.

Natural language interfaces

Add conversational interfaces to existing products. Query databases, trigger workflows or get guidance without learning a new system.

Existing product integration

Adding AI to a product you already have. We handle model selection, prompt engineering, testing and production monitoring so the feature ships reliably.

How we work

Discovery. We start by understanding what you're trying to automate or improve. We'll challenge assumptions, identify what AI can and can't do reliably and propose an approach that fits your constraints.
Prototype. Before committing to a full build, we prototype the core AI interaction. This is where you find out what prompt strategies work, what the failure modes are and what accuracy looks like in practice.
Build. We build production-grade software around the AI. That means proper error handling, logging, testing and infrastructure. Not a demo. Something you can rely on.
Iterate. AI products improve with use. We stay engaged to refine outputs, tune prompts and evolve the system as your needs change.

Background reading

These articles give a sense of how we think about AI and the problems it solves well.

What are AI agents? A practical explanation of agentic systems and when to use them. AI-assisted coding A look at the tools and approaches reshaping how software gets written. AI glossary Plain-English definitions of LLMs, RAG, embeddings, temperature and the rest of the jargon. Machine learning models A guide to the model landscape and how to pick the right one for the job.

If you've got an AI project in mind and want to talk through what's feasible, get in touch.

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