TL;DR
Faculty AI has deep machine learning expertise, unusual credibility in safety and public-sector work, and experience delivering large AI programmes. Squirrel AI is built for mid-market PE value creation: senior builders inside the portfolio company, short production cycles and accountability to the P&L within a hold window.
What Faculty AI is
Faculty was founded in 2014 and is one of the UK's best-known applied AI firms. It has served more than 350 customers and is strongest in government, healthcare, defence and large enterprise. Its publicly cited work includes NHS England, the Home Office and Tesco.
The firm also conducts AI safety testing with frontier labs including OpenAI and Anthropic. Its respected Fellowship programme has trained hundreds of data scientists, contributing technical talent to Faculty and the wider UK market.
Faculty has invested in internal delivery platforms to industrialise how AI systems are shipped. In January 2026, it was announced that Faculty would be acquired by Accenture. Buyers evaluating the firm today are therefore also evaluating what delivery looks like as part of a global consulting group.
Where Faculty is genuinely strong
Faculty is not a strategy house dressed as an engineering company. It has genuine machine learning depth and experience running complex programmes where model performance, safety and organisational controls all matter.
Its government and public-sector record carries weight. Working in environments such as healthcare, defence and central government requires procurement discipline, careful risk management and the ability to operate across large stakeholder groups. Few independent AI firms have comparable safety credentials.
The investment in internal delivery platforms is also a smart idea. Reusing tested components and methods can improve consistency and avoid rebuilding the same technical foundations for each client. For organisations planning several large AI programmes, that industrialised approach can be valuable.
The Accenture acquisition expands the potential scale and reach around Faculty. It can give clients access to more capabilities, geographies and enterprise relationships. Those are real advantages for a multinational or government buyer that needs a large programme delivered through established procurement channels.
Where the model differs for PE portfolios
Faculty's centre of gravity is government and large enterprise. Those buyers tend to commission procurement-grade programmes with longer cycles, formal change management and several organisational layers. That is a different muscle from mid-market PE value creation.
In a portfolio company, the buyer may be an operating partner while the budget sits with management. The clock is the hold period. The relevant measure is not whether a programme was delivered to specification, but whether it increased revenue, reduced cost or changed working capital early enough to affect the exit case.
The announced acquisition makes the distinction worth testing directly. A global consulting group can offer more scale and reach. It also has more organisational layers. Buyers should ask how those features affect the named delivery team, contracting process, decision speed and ownership of a small but commercially material build. There is no need to speculate beyond those practical questions.
Mid-market and PE-backed businesses are exactly where we live. We are often brought in after a larger consultancy or AI house has completed an assessment, recommendation phase or platform engagement, with workflow-level building still to do. Executives describe intelligent, well-formatted reviews that reached the executive team but left data readiness, dependencies and priorities unresolved. This is a general pattern across staged advisory models, not a claim about any named Faculty project.
How Squirrel AI is different
An AI value creation partner to PE funds and their portfolio companies. We go into the portcos and build, rather than advising from the sidelines, and everything we build is aimed at the P&L.
Our founders spent almost a decade in investment roles at firms including Apax, 3i and Deutsche Bank before crossing to the operating side. We were investors ourselves before this, so we cover the commercial side as well as the technical.
Delivery is partner-led. The same senior people scope, prioritise and build. A trusted offshore engineering bench provides extra capacity, but the commercial judgement and client relationship remain with the founding team. That matters when management changes its view after seeing the first working version, or when a data limitation makes the original use case unattractive.
Our first scoped engagement typically lasts three to four weeks and finishes with a production deliverable. We attach a number to every build. For a Series A insurtech, for example, we built AI document intake that is core to the product. At Healf, the FT's #1 fastest-growing company in Europe, the founding team led AI work that added over £10m of annualised revenue to a business running at £100m. The fastest project paid back in twelve weeks.
We charge materially less for the same outcome because our model is lighter, not because the work receives less senior attention. There is no pyramid of junior consultants or global brand overhead. More of each pound goes to the people doing the work, so partner-led delivery supports both quality and cost.
Who should choose Faculty, and who should choose us
Choose Faculty for government, regulated enterprises and organisations that need unusual safety credibility, procurement-scale delivery or a large applied AI programme. Its technical depth and experience with complex institutions are strong reasons to buy.
Choose Squirrel AI for a PE fund or portfolio company that needs senior builders, fast payback and P&L accountability inside a hold window. We fit best when the problem sits inside a real workflow, management needs help choosing what matters, and a working system is more useful than another platform or programme layer.
Three questions to ask either of us
- Who exactly will do the work, and will the senior people in the sales process remain responsible during the build?
- What will be running in production by week six, and which data, approvals or system dependencies could prevent that?
- What number will the work put on the P&L, when will it be measured, and who owns the result after deployment?
If your question is whether one portco workflow can create measurable value this quarter, book a 30 minute call. Bring the workflow, its current baseline and the hold-period context. We will tell you whether it merits a build.