Large language models are powerful, but on their own they do not know your business. We connect them to your documents and data, so every answer is grounded, current and traceable.
We build retrieval-augmented generation (RAG) systems that search your content before they answer and cite their sources, and we choose, prompt, evaluate and where useful fine-tune the model that fits your cost, speed and privacy needs.
What we deliver
- Knowledge assistants grounded in your documents
- Semantic search across files, wikis and tickets
- Summaries, reports and first drafts at scale
- Model selection, prompt design and fine-tuning
- Evaluation sets that measure accuracy before launch
- Private deployments that keep your data in your control
Ideas we can bring to life
Ask-your-company search
Employees ask a question in plain language and get an answer drawn from policies, manuals and past projects, with links to the sources.
Report and proposal writer
Turns notes, data and templates into consistent first drafts that your experts review and finish.
Multilingual content
Translates and adapts product information, support articles and messages for every market you serve.
Conversation insights
Summarises support chats and calls, spots recurring problems and suggests answers for the next customer.
Technologies we work with
- Anthropic Claude
- OpenAI GPT
- Google Gemini
- Llama and other open models
- Python
- TypeScript
- Vector databases
- Google Cloud
- AWS
- Azure