Service
LLM application development
Large language models can make a product dramatically more useful, but only when the feature is designed around what users actually need to get done. We build LLM features that are grounded in your data, measurable and pleasant to use.
That covers the full stack: retrieval pipelines, prompt and model selection, structured outputs, evaluation, and the interface people interact with.
Where it helps
- Customer-support copilots that cite your knowledge base
- Internal knowledge assistants for policies, wikis and documentation
- Generative features inside an existing SaaS product
- Extracting structured data from emails, PDFs and forms
What we build
Retrieval-augmented generation (RAG)
Answers grounded in your documents and data, with citations so users can check the source.
Copilots and assistants
In-product assistants that help users write, analyse and act without leaving your app.
Semantic search
Search that understands meaning, across documents, tickets, code and knowledge bases.
Structured outputs and extraction
Turning unstructured text into validated data your systems can use.
Model selection and evaluation
Benchmarking frontier and open-weight models on your tasks for quality, latency, cost and data residency.
How we deliver
- 01
Discover
We map your workflows, data and constraints to find the highest-leverage AI opportunities.
- 02
Prototype
Within weeks you get a working prototype tested against real data and a clear evaluation baseline.
- 03
Engineer
We harden the system: security, evals, observability and a UX your team actually wants to use.
- 04
Scale
We ship to production, monitor quality and costs, and keep improving as models evolve.
LLM-Powered Products: common questions
What is RAG and do we need it?
Retrieval-augmented generation lets a model answer from your own documents instead of only its training data. You need it when answers must reflect your current, private information.
Which language models do you use?
We are model-agnostic. We compare frontier and open-weight models on your use case and choose based on quality, latency, cost and where your data may be processed.
Will our data be used to train AI models?
We never use client data to train third-party models, and we can deploy within your own cloud account when required.
Related services
- AI Agents & AutomationAutonomous agents that plan, use tools and complete multi-step work across your systems — with humans in the loop where it matters.
- Product EngineeringFull-stack web and mobile platforms engineered for reliability, accessibility and speed.
- Websites & Local SearchWebsites and Google profiles that help local businesses get found and called, with every call and request measured.
Let's talk about llm-powered products
Tell us what you want to build. We reply within one business day with honest advice and next steps.