We build LLM Integration & Retrieval Systems
We embed language models and retrieval into your products and operations, so they answer from your knowledge, your documents and your data, accurately and with sources. Grounding is the whole job: we build the retrieval, the citations and the checks that stop a confident wrong answer reaching a user, and we keep the running cost sane in production.
- Grounded in your knowledge
- Embedded where it helps
- Accurate and traceable
- Engagement
- Fixed scope or embedded team
- First build
- Usable version in weeks, not quarters
- After launch
- We stay on to evolve it
The problems we're built to solve.
Your AI confidently makes things up
An ungrounded model gives fluent, plausible answers that are simply wrong. Users can't tell the difference, until it costs them.
The consequence:
One bad answer is all it takes for people to stop trusting the whole feature.
Your knowledge is locked in documents no one reads
The answers your team and customers need are buried across wikis, PDFs and tickets. If it can't be found in the moment, it may as well not exist.
The consequence:
The same questions get asked again and again while the real answers gather dust.
Generic AI doesn't know your business
An off-the-shelf chatbot has no idea about your products, policies or data. It answers in general terms when your users need specifics.
The consequence:
You get a novelty that impresses once and helps no one twice.
The stack we reach for on llm integration & rag.
Why LLM Integration & RAG?
Grounded in your knowledge
Retrieval-augmented generation keeps answers tied to your real documents and data, cutting hallucination and building trust.
Embedded where it helps
Search, drafting and summarisation woven directly into your product and workflows, not left in a separate chat window.
Accurate and traceable
Answers come with sources and confidence, so your team and customers can verify what the model tells them.
Why us?
Retrieval done right
We have built RAG and knowledge systems that stay accurate at scale. Getting retrieval, chunking and evaluation right is subtle work we do every day.
A team powered by agentic engineering
Because we build with these tools constantly, we know which models, embeddings and patterns fit your problem, and how to keep costs sane in production.
Quality of delivery, guaranteed
Grounded, evaluated and monitored. We deliver LLM features that hold up on real questions from real users, and keep them accurate as your data grows.
Book a call about your llm integration & rag project.
Grab 30 minutes with us. Bring the problem you're solving and we'll come back with how we'd approach it.
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