Professional AI consulting practice
Rubytech is a professional AI consulting practice. We help complex organisations put AI to work, safely reduce that complexity, and improve operational efficiency. We work with business, division and product leaders to maximise the return on your AI deployment, with people in control at every step.
What we do
Most organisations do not need another pilot. Business, division and product leaders need one clear win, a data foundation worth building on, and a way to scale that does not break what already works. We help you put AI to work where it improves operational efficiency, and where the return is plain. That is the work we do.
We start by finding the project with the quickest, clearest return, then prove it before anyone commits to a wider programme.
We give your information one trusted home, so AI works from facts your team agrees on rather than from scattered copies.
Every workflow we build runs under human review. The operator decides what happens; the system does the heavy lifting.
AI consulting services
A clear set of services, each tied to an outcome you can measure and to the return on your AI deployment. We take on as much or as little of the work as you need, from a first opinion to running the system day to day.
We map where AI can genuinely help, rank the options by return and effort, and give you a short, honest plan you can act on.
Outcome: a costed shortlistWe automate the repetitive, rules-heavy work, the reconciliations, the chasing, the re-keying, so your people spend their time on judgement, not admin.
Outcome: hours returnedWe build a single, trusted source for your information, so every system and every model reads from the same agreed set of facts.
Outcome: one source of truthWe connect the tools you already run so they work as one. No more manual hand-offs between systems that were never meant to talk.
Outcome: fewer manual hand-offsWe put clear ownership, oversight, and records around every AI system, so you can show a regulator exactly how a decision was made.
Outcome: defensible decisionsWe do not stop at the slide deck. We build, deploy, and, where you want it, run the system so the value actually lands.
Outcome: systems in productionOur approach
We earn the right to do more by getting the first thing right. The method is the same every time: reduce complexity, improve operational efficiency, and keep a person in control at every step.
We learn how the work really gets done and where the time and money leak away.
We choose the project with the highest return for the least effort and risk.
We give your data one trusted home so everything after it stands on firm ground.
We put orchestration and agents to work, with a person reviewing and approving.
Once one project pays for itself, we extend the same foundation to the next.
People stay in control. The system handles the volume and the repetition; your operators set the rules, review the work, and hold the final say. That is how AI belongs in a regulated business.
Insights
Short, plain pieces on the questions our clients ask most: what the new rules mean, what responsible AI looks like in practice, and why more integrations rarely fix a fragmented business.
The rules are set. The work of preparing for them is not.
Europe's AI law sorts systems by how much harm they could do, and the heavier the risk, the more you have to prove. If you operate across borders, the safest move is to treat the strictest rule as your baseline everywhere.
Start now with a plain inventory: which AI systems you run, what each one decides, and who owns the outcome. Most of the effort is records and oversight, not new technology, and those take time to put in place.
Read the view →Responsible AI is less about principles on a wall and more about who answers when something goes wrong.
The questions that matter are simple. Who owns this system? What data trained it? Can we explain a decision to the person it affected? Can we show our working to a regulator?
Done well, this is not a brake on progress. Clear ownership and good records are what let you scale AI with confidence instead of crossing your fingers.
Read the view →Each new connection between two systems is one more thing to maintain, and one more place for the numbers to disagree.
When every tool holds its own copy of the truth, your team spends its days reconciling. Wiring the tools together more tightly just moves the mess around.
The durable fix is a shared data foundation: one trusted source every system reads from. AI then works from facts your people already agree on, and the reconciliation simply stops.
Read the view →About Rubytech
Rubytech is a professional AI consulting practice. We help organisations where the stakes and the rules are high: financial services, healthcare, insurance, and operations that span more than one jurisdiction.
We bring significant experience across sectors and business stage, so we have seen your kind of problem before. It comes from combined work across banking, insurance, data, science, and complex multi-system operations, the kind of environments where a wrong answer is expensive and the regulator is watching. We have built the systems and we have answered for them, on both sides of the table.
That depth shows up as judgement: knowing which problem is worth solving first, which data you can trust, and where AI earns its place rather than adding risk. We work alongside business, division and product leaders to maximise the return on your AI deployment, as senior independent consultants, so you deal with the people doing the thinking, not a chain of hand-offs.
The proof is in what we have built. Our own products run on Anthropic's Claude models in production, day to day. The work below is the evidence under the capability, not a portfolio of slides.
We provide services in the United Kingdom and across the EEA.
Selected work
We do not just advise on AI. We build and run it. These are our own products, live today and used every day, built principally on Anthropic's Claude models. They are the evidence behind the consulting.
A full working AI environment we install on a client's own server: Claude Code joined to a persistent knowledge graph that holds every person, document, conversation, and decision they have touched, with email, messaging, research, and document production wired in. It is the working version of the architecture we recommend to clients, built by us and run by us.
Claude Code · knowledge graph · agent orchestration getmaxy.com → EducationA hands-on course, in London and online, that teaches knowledge workers to set Claude up around their own work without writing code. Twenty-eight modules across five stages, from the basics of the models through bringing your archives into a structured data layer to running the whole setup day to day. It is our applied Claude knowledge, written down and taught.
Claude fundamentals · data layer · applied practice maxy.institute →Start a conversation
A first conversation costs you nothing but an hour. We will tell you honestly whether AI is the right answer for the return you are after, and if it is, where to begin.