Nobody owns us, so nobody picks your model.

Applicat AI is an independent frontier applied AI company. The founders own it: no AI lab, no cloud provider, no consultancy, no investment fund, and no software licence of our own to protect. So the model that ends up in your system is the one that won on your own cases, what we learn about your operation stays inside your business, and when the honest answer is that you should not build the thing, we are free to say so.

Talk to us See the Frontier log

Fig. 01Ask every firm the same questions

01Who picks the model
02Who owns the firm
03Who they serve
04What you commit to first
05Where your knowledge goes
06What happens after go-live

What changed in 2026

The model companies became the services companies.

In five months the AI labs, the clouds and the largest consultancy all moved into AI deployment. For the biggest enterprises that is good news. It also means the firm sitting inside your operation now has a model of its own to place.

16 March 2026
Accenture
Completed its acquisition of Faculty, the London applied AI company, bringing more than 400 AI-native professionals and the Frontier decision intelligence product into the consultancy.
Source: Accenture newsroom
4 May 2026
Anthropic, Blackstone, Hellman & Friedman and Goldman Sachs
Announced a joint venture of around $1.5 billion to build an enterprise AI services firm that embeds engineers and Claude models into mid-sized companies, with private equity portfolio companies as the natural first market.
Source: TechCrunch
11 May 2026
OpenAI
Launched the OpenAI Deployment Company with $4 billion of initial investment from 19 firms led by TPG, and agreed to acquire Tomoro, an applied AI consultancy with around 150 forward-deployed engineers.
Source: OpenAI
2 July 2026
Microsoft
Launched the Microsoft Frontier Company, an operating business with a $2.5 billion commitment and 6,000 industry and engineering experts, to deploy AI inside enterprise operations.
Source: TechCrunch
15 July 2026
Ode with Anthropic
The Anthropic joint venture launched publicly as a standalone services firm, led by chief executive Chris Taylor, targeting mid-sized organisations across financial services, healthcare, retail, manufacturing and software.
Source: Business Wire

Three questions a buyer now has to ask.

01
Who chooses the model
A deployment team owned by an AI lab deploys that lab's models. That may well be the right answer for your problem, but nobody has tested whether it is. The strongest model for reading documents, for voice, for code and for long reasoning work is rarely the same one, and the order changes every few months.
02
Where your knowledge ends up
A team working inside your operation learns how it really runs: the exceptions, the workarounds, the judgment nobody has written down. Boards have started asking where that understanding goes when the engagement ends, and whether a firm that also serves your competitors should be the one holding it.
03
Who they were built to serve
The new deployment ventures are aimed at the Fortune 500, the FTSE 100 and private equity portfolios, with minimum engagements reported in the millions. Mid-sized enterprises have the same processes, the same regulators and the same need for systems that hold up in production. Almost none of that new capacity points at them.

What independence means in writing.

Six things we put in the contract. Hold us to any of them.

We test the models on your work first

In the first weeks your own cases go through several candidates: frontier models from Anthropic, OpenAI and Google, and the open models where data residency, cost or speed favour them. You see the scores. The one that goes into your system is the one that won, and it can change when a better model arrives.

What you tell us stays yours

The code, the data, the prompts and the test cases are yours in the contract. We commit not to reuse what we learn about your operation on another client, and nothing of yours goes into training a shared model.

Nobody holds a share of us but the founders

No outside investor holds equity in Applicat AI, and that includes the AI labs, the clouds, the consultancies and the funds now buying their way into this market. If it ever changes, this page will say so before we say it anywhere else.

Sized for organisations that decide in a room

Scope, pace and price are set for mid-sized enterprises, and we go to them directly. That is why the first thing we ask you to commit to is a fixed-fee sprint of four to six weeks, at the end of which you can walk away with what we built.

Independent enough to say no

The Prove stage ends with a written go or no-go. We sell no models and no licences, so a no costs us the work and nothing more, and it saves you from the expensive maybe.

Accredited with the labs, exclusive to none

We pursue accreditations with the AI labs and clouds our clients use, and we have never traded one for exclusivity. Accreditation tells you we know a platform; independence tells you we will still choose the right one.

Ask every firm the same questions. Compare the answers in writing.

Who picks the model
Applicat AI
Whichever model wins on your own cases, frontier or open
Lab-owned deployment companies
The owning lab's models
Cloud provider deployment units
The owning cloud's catalogue
Global consultancies
Broad, shaped by alliances
Who owns the firm
Applicat AI
The founders, and nobody else
Lab-owned deployment companies
An AI lab plus investment funds
Cloud provider deployment units
The cloud provider
Global consultancies
Publicly listed or a partnership
Who they serve
Applicat AI
Mid-sized enterprises, engaged directly
Lab-owned deployment companies
Fortune 500, FTSE 100, PE portfolios
Cloud provider deployment units
Existing enterprise cloud accounts
Global consultancies
Large enterprise and public sector
What you commit to first
Applicat AI
A fixed-fee sprint of four to six weeks
Lab-owned deployment companies
Reported minimums in the millions
Cloud provider deployment units
Tied to a platform commitment
Global consultancies
A programme of work
Where your knowledge goes
Applicat AI
Nowhere: you own the assets, we do not reuse your process knowledge
Lab-owned deployment companies
Set by the AI lab's terms
Cloud provider deployment units
Set by the cloud's terms
Global consultancies
Firm-wide knowledge reuse is the model
What happens after go-live
Applicat AI
We stay on the system, with a written report every month
Lab-owned deployment companies
Varies by engagement
Cloud provider deployment units
Tied to platform consumption
Global consultancies
A managed services arm takes it on

How Applicat AI compares with lab-owned deployment companies, cloud provider deployment units and global consultancies
Question	Lab-owned deployment companies	Cloud provider deployment units	Global consultancies	Applicat AI
Who picks the model	The owning lab's models	The owning cloud's catalogue	Broad, shaped by alliances	Whichever model wins on your own cases, frontier or open
Who owns the firm	An AI lab plus investment funds	The cloud provider	Publicly listed or a partnership	The founders, and nobody else
Who they serve	Fortune 500, FTSE 100, PE portfolios	Existing enterprise cloud accounts	Large enterprise and public sector	Mid-sized enterprises, engaged directly
What you commit to first	Reported minimums in the millions	Tied to a platform commitment	A programme of work	A fixed-fee sprint of four to six weeks
Where your knowledge goes	Set by the AI lab's terms	Set by the cloud's terms	Firm-wide knowledge reuse is the model	Nowhere: you own the assets, we do not reuse your process knowledge
What happens after go-live	Varies by engagement	Tied to platform consumption	A managed services arm takes it on	We stay on the system, with a written report every month

General patterns as reported publicly in 2026. Any specific engagement may differ; ask each firm the same questions and get the answers in writing.

Read the full analysis with sources

FAQ

Questions about independence

Three things change. The model is picked by testing it on your work, because nobody here has a licence riding on the answer. Your process knowledge and everything built with it stay yours under contract. And the engagement is sized for your organisation, where the new deployment ventures start at reported minimums in the millions. Plenty of organisations will end up using both, with the independent firm running the testing and running the system after go-live.

We build on their frontier models through enterprise programmes, and we pursue accreditations with the AI labs and clouds our clients use. We have never traded an accreditation for exclusivity. Which model goes into a client's system is settled by running that client's own cases through the candidates.

Independence is a structure, not a size. Applicat AI has a globally distributed engineering team and was founded by the team behind BroadVision Technologies, which has delivered enterprise IT for more than 26 years. Every engagement is staffed with named engineers, and the Run stage carries service levels you can hold us to.

It stays with you. You own the code, the data, the prompts and the test cases, in the contract. We commit not to reuse your process knowledge on another client, and nothing of yours goes into training a shared model. End the relationship and your team keeps everything it needs to carry on.

Ask us the questions on this page.

Tell us the process you want to change. We will tell you which models we would test it on, what you would own at the end, and what it would cost.

Talk to us See how we work

The model companies became the services companies.

Three questions a buyer now has to ask.

Who chooses the model

Where your knowledge ends up

Who they were built to serve