Systems that run the work, not demos of it.
Most AI projects stop at a pilot that impresses a room and changes nothing. We build the version that runs on Monday: agents, workflow automation and custom LLM applications, wired into the stack you already pay for, measured against the numbers you had before we started.
Tell us the process. You get a scoped plan back, with a build shape and a timeline
26 systems, one way of working
Each of these is a build, not a retainer for advice. Nine of the thirty are below. The rest are on the services page, grouped by the part of the business they sit in.
AI Agent Development
Agents that plan, call tools and verify their own output, built for one job and measured against it.
View service →02Multi-Agent Systems
Several specialised agents with a supervisor, for work too varied for a single prompt to hold.
View service →03Workflow Automation
The connective tissue between your tools, so a process runs without anyone shepherding it.
View service →04Business Process Automation
Whole processes rebuilt end to end rather than a script bolted onto the worst step.
View service →05RPA Replacement
Replacing brittle click-recording bots with systems that read intent instead of screen coordinates.
View service →06Agent Observability
Logging, tracing and replay so you can see what an agent decided and why, months later.
View service →07Custom LLM Applications
Software with a model inside it, built for your data and your workflow rather than a generic chat box.
View service →08RAG and Knowledge Systems
Retrieval that answers from your documents with citations, and admits when it does not know.
View service →09Model Fine-Tuning
Adapting a model to your domain when prompting has genuinely run out of room, and not before.
View service →Six stages, and you can stop after any of them
Nothing here requires a leap of faith. Each stage produces something you can look at and judge before the next one starts.
Frame
We map the process as it actually runs, not as the org chart says it runs. Every handoff, every exception, every place a human is copying between two screens.
Instrument
Before anything is built we measure the current state: volume, cycle time, error rate, cost per run. Without this there is nothing to compare against later.
Build
The system gets built in slices, each one shipped and used. You see working software early and often rather than a reveal at the end.
Prove
We run the system alongside the humans doing the work and compare against the baseline. If it is not better, it does not ship. That is the whole test.
Hand over
Documentation, runbooks, an owner on your side who understands how it works, and the credentials in your name. No hostage situations.
Compound
Once one process is automated the next one is cheaper, because the plumbing already exists. This is where the return actually comes from.
Six positions we actually hold
These are the ones that cost us work sometimes, which is how you know they are real rather than decoration.
We build engines, not experiments
A demo proves a model can do something once. An engine does it every day, at your volume, with the failures handled. Only one of those changes a P&L.
The baseline comes before the build
If nobody measured the process before it was automated, nobody can honestly say the automation worked. We measure first, every time, even when it delays the fun part.
You own everything
Code in your repository, keys in your accounts, documentation written for your team. If you fire us on a Friday the system still runs on Monday.
A human stays in the loop where it matters
Full autonomy is the right call for a tagging job and the wrong call for anything that touches money, hiring or a customer relationship. We put the review step where the risk is.
Small slices, shipped early
Long builds hide bad assumptions. Shipping a thin version in week two surfaces the problems while they are still cheap to fix.
We tell you when not to automate
Some processes are too rare, too variable, or too close to a judgement call. Automating those buys you a fragile system and a maintenance bill. We say so before you spend.
Boring where it counts
We pick the least exciting tool that does the job, because the interesting one is usually the one nobody can maintain in eighteen months. Models get swapped as they improve. The plumbing around them is built to outlast them.
How this actually gets done
Written for the person who has to implement it, not for the person approving the budget. Frameworks, worked arithmetic, and the parts that usually go wrong.
How to Pick the First Process to Automate with AI
Most first automations are chosen by whoever complained loudest. Here is the selection method that survives co
Read →Getting startedThe AI Automation Readiness Check, Run in an Afternoon
A readiness questionnaire measures optimism. These five probes measure your systems. Run them in one afternoon
Read →Getting startedWhy AI Pilots Fail: The Gap Between a Demo and Production
A pilot and a production system share a model and almost nothing else. Here are the five gaps that strand good
Read →Getting startedBuild, Buy or Wait: How to Choose Your AI Approach
Build versus buy is really six decisions, one per layer of the stack. Here is where to draw the line, what wai
Read →Getting startedWriting an AI Automation Brief Your Vendor Can Price
A vendor cannot price what you have not decided. This is the brief that turns a vague automation idea into a f
Read →Getting startedHow to Map a Process Before You Automate It
Swimlane diagrams do not stop automations from failing. What stops them is knowing the exception distribution
Read →The questions that come up first
What does a first project usually look like?
How is this different from buying an AI tool?
Do we need clean data before we start?
What if the system gets something wrong?
Who owns the code and the accounts?
How do you price this?
Send us the process that is eating the most hours.
Not a brief, not a deck. Just describe what happens today, who does it, and roughly how often. A scoped plan comes back with the build shape, the stack and a timeline.
Start a project →