Frontier applied AI company
Pick a process that is costing you real money. We build a working AI system into it, on your own data, usually inside six weeks. You own what we build, it runs on your systems, and we are still accountable after it goes live. Nobody owns us, so nobody picks the model for us.
The Applicat AI mark: an outer circle representing your organisation, containing two overlapping lenses, one for the frontier models and one for your operation. The point where they meet is what is running in production.
Who we build for
Mid-sized enterprises run real operations at real volume and can still decide quickly. What they rarely have is an AI engineering team of their own. The deployment arms of the AI labs, the clouds and the global consultancies are built for much larger organisations, so this is the part of the market we built the company to serve.
Thousands of documents, requests and decisions a month, sitting inside processes your leadership already measures. Enough volume for a system to move a number, and a small enough estate to move it this year.
Engineers who have put AI into production are scarce, expensive and hard to keep current as the frontier moves. We bring named ones to the engagement and hand the capability to your people as we go.
One sponsor, one working group, one room. That is what gets an engagement from first conversation to a working system on real data in weeks, while a larger organisation is still booking its second steering committee.
How we engage
Each is fixed in scope and ends in a decision you make on evidence. Start where the risk is, and carry on only if the numbers say so.
Frame and Prove
01
Four to six weeks, fixed scope and fixed fee. We work out which of your processes is worth doing first, then build a working version of it on your real data, inside your own environment. You get a straight recommendation at the end, including the recommendation to stop.
Build and Deploy
02
Turning that proof into something your business can lean on. It connects to the systems you already run, respects who is allowed to see what, keeps a record of every decision it makes, and passes your security review. Then we roll it out with the people who will use it.
Run
03
Someone has to own the thing at three in the morning. Accuracy and cost are watched daily, a new model is tested on your cases long before it goes near your users, and you get a written report every month against the number we agreed at the start.
Why this is hard
These are other people's numbers, with the sources attached. They are the reason this company is built the way it is.
Three commitments
Every firm will tell you it is experienced and outcome-focused. These are the ones you can check.
01
Applicat AI is founder-owned. In 2026 the AI labs and the big clouds started selling deployment themselves, and a deployment team owned by a lab deploys that lab's models. We have no licence to protect. So we can test four models on your work, tell you the cheapest one won, and tell you when you should not build the thing at all.
02
What we build runs in your own environment, on your accounts, under your security. The code, the data, the prompts and the tests are yours in the contract, and your process knowledge does not travel to anyone else. End the relationship tomorrow and the system keeps running, with your team holding everything they need to change it.
03
A delivery firm hands over and invoices. We stay on the system: accuracy and cost watched, every change re-tested on your own cases, new models proven before they reach your users, and a written report each month against the number we agreed before we started.
In 2026 the AI labs and the clouds became deployment companies, and everyone started claiming to be model-agnostic. Here is ours in the three places a buyer can hold us to it.
Proof
Applicat AI is a young company, and pretending otherwise would be the first thing to distrust about us. So instead of logos, two things: what this work looks like inside an organisation, and the facts about us you can verify before you commit to anything.
Specialty insurance
Industrial distribution
Engineering and construction
These are engagement shapes, drawn from the kinds of operation the Applicat Method is built for. No client is named and no result is claimed, because we would rather show you the work than a number you cannot audit.
01
02
03
04
Case studies. Named case studies will appear here as engagements complete and clients agree to be named. Until then, we will introduce you to a reference directly, which tells you more than a paragraph we wrote ourselves.
Business Operating System
Buying AI one tool at a time leaves an estate of vendors, each with its own copy of your data, its own permissions and its own version of the truth. The alternative is a layer you own, running in your own environment, where your people build.
01
Connections, permissions, model access and the record of what happened live once in your own environment, instead of once inside every vendor you buy from.
02
Your engineers and the teams closest to a process build on it, inside limits the layer enforces. Ours build the first systems and the difficult ones.
03
Nothing is bought in advance. Each part is built the first time a real system needs it, and the second and third systems are what turn it into a layer.
What we build
Multi-step work run end to end by agents, with your people at the checkpoints that matter.
Reading, sorting, checking and reconciling contracts, claims, invoices and forms.
Triage, resolution and help for the person on the call, in contact centres and service desks.
Assistants that answer from your own policies and systems, and show where each answer came from.
Answers from governed data, and reports that do not have to join a queue.
Products built for your business, from the tests that prove them to the screen your people use.
The Applicat Method
Five stages. Each produces something you can look at, and each ends in a decision you make. The first four to six weeks put a working system on your own data.
01
Frame
What is worth building, ranked
02
Prove
A working system on real data
03
Build
Integrations, limits, tests that gate every change
04
Deploy
Rollout, training, adoption
05
Run
Operations and monthly value reporting
Independent, with deep roots. Founded by the team behind BroadVision Technologies, a global IT services company with more than 26 years of enterprise delivery. About Applicat AI
FAQ
Tell us about the process you want to change. We reply within one business day.