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New: AI Operators. An AI teammate in the tools your team already uses

/ Service · Our Specialism

AI Systems.

AI assistants, RAG and knowledge systems, workflow automation, document understanding, semantic search, and AI features built into real products. Not a chatbot bolted onto a homepage - intelligence engineered into the work, grounded in your data, tuned for production.

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/ Overview

There's a wide gap between a demo and a system you can rely on. A lot of 'AI features' are a model wired to a prompt that works in a screenshot and falls over in the real world. We build the other kind: grounded, evaluated, and engineered to hold up at scale.

Because we also design and build the surrounding product, the AI doesn't sit awkwardly to one side. It lives where the work actually happens - inside your flows, your data and your operations - so it does more, costs less to run, and pulls ahead of the competition.

/ What it covers

Where it pays off, we build AI in.

  • 01

    AI assistants & copilots

    In-product assistants that help users do real work, grounded in your data and your domain rather than generic and guessable.

  • 02

    Workflow automation

    Agents and pipelines that remove manual work - triage, generation, classification, follow-up - running reliably in production.

  • 03

    Retrieval (RAG) & knowledge systems

    Answers anchored to your documents, catalogue and history - traceable and verifiable, not improvised by a model guessing.

  • 04

    Document understanding

    Extracting structure and meaning from contracts, forms, reports and unstructured files at a scale no team could do by hand.

  • 05

    Recommendations & personalisation

    Surfacing the right content, product or next action for each user, built on your real data.

  • 06

    Semantic & natural-language search

    Search that understands intent rather than matching keywords, across your own content and data.

  • 07

    Model selection & evaluation

    Choosing the right model for each task and building the evaluation harness that proves it works before it ships.

  • 08

    AI strategy & feasibility

    An honest read on where AI will and won't pay off in your product, so you invest where there's genuine leverage.

/ What you get
  • Working AI feature in your product
  • Grounded, evaluated model pipeline
  • Evaluation & quality harness
  • Documentation of methodology & data
  • Monitoring & cost controls
  • Roadmap for further enhancement
/ How it runs

  1. Find the leverage

    We identify where intelligence genuinely helps - a process to automate, a decision to sharpen - and where it doesn't. You only invest where it pays off.

  2. Ground it

    We connect the system to your real data through retrieval and structured context, so outputs are anchored and verifiable rather than invented.

  3. Engineer & evaluate

    We build the pipeline and the evaluation harness together, so quality is measured, not assumed, before anything reaches users.

  4. Ship & monitor

    It goes live with monitoring and cost controls in place, and we tune it as real usage teaches us where it can do more.

/ Questions
Is this just adding a chatbot to my site?

No - and that's rather the point. A chatbot bolted to a homepage is the version that gets clicked once and forgotten. We build intelligence into the places where the work actually happens, grounded in your data, where it creates measurable leverage.

How do you stop the AI making things up?

We ground systems in your real data using retrieval and structured context, so answers are anchored to verifiable sources rather than improvised. We also build evaluation harnesses that test quality before anything ships, and monitoring that catches problems in production.

Which AI models do you use?

We choose the model to fit each task - tuned for cost, latency and quality - and engineer the system around it rather than the other way around. We work with current frontier models and select based on what the job actually needs.

Do I need a lot of data to start?

Not necessarily. Many high-value AI features work from the data and documents a business already has. Part of our job is an honest feasibility read - telling you what's possible with what you've got, and what would need more.

Can you add AI to a product you didn't build?

Yes. We can integrate AI capability into an existing product, or design and build the surrounding experience as well if the feature needs it to land properly.

/ Start here

Let’s build
it properly.

Tell us what needs to change. We will come back with a route, a timeline and a number.

Book a call

Related: launch sprint, build, ai automation support maintenance retainer