The enterprise AI bill is enormous, but the return on investment is often a slide deck. Valliance, a new consultancy that launched this year with $15 million in private equity backing, is built on the premise that the traditional consulting model is structurally broken for delivering production-grade AI [Finextra, Feb 2025]. Its founders are betting that large enterprises will pay for a different kind of service, one that only gets paid when value is created in a live system, not when hours are logged.
A commercial model as the wedge
Valliance's primary differentiator is its commercial terms. The firm has explicitly moved away from time-based billing, adopting a value-based fee structure where clients pay when a project delivers measurable value in production [Finextra, Feb 2025]. This is a direct challenge to the economics of legacy consultancies, which Valliance claims waste more than £66 billion annually of UK enterprise AI spend [UK Tech News, Nov 2025]. The model aligns the consultancy's incentives with the client's success: if the AI system doesn't work in production, Valliance doesn't get paid in full.
The team built for delivery
The founders are not first-time operators. Each brings a track record of building and selling consultancies focused on technical implementation.
| Founder | Prior Role & Exit | Domain Expertise |
|---|---|---|
| Tarek Nseir | Founded TH_NK, acquired by EPAM Systems | Digital transformation |
| Anita Rajdev | Commercial leader at EPAM Systems and TH_NK | Enterprise partnerships |
| Rad Parvin | Founded Just-BI, acquired by Informatica | Global data strategy |
| Dom Selvon | Co-founder of the composable architecture movement | System architecture |
Scaling a specialist bench
Valliance launched with a core team of 15 specialists and plans an aggressive hiring spree, aiming to bring on 80 AI specialists by 2026 [Osborne Clarke, 2025]. The revenue target is €100 million by 2030 [Osborne Clarke, 2025]. The early traction signal is three signed clients, though their names have not been disclosed [TechFundingNews, Feb 2025].
The technical breakdown and scale risks
The value-based model introduces several technical and operational complexities. Defining "value" and "production" requires clear, upfront contracts and shared metrics. The consultancy must also architect systems for long-term maintainability, as its payout may be tied to ongoing performance.
- Contract friction. Negotiating value-based terms for every enterprise engagement is slower and more legally complex than selling a block of hours.
- Revenue recognition. The firm's income will be lumpy and tied to project milestones or ongoing system performance.
- Specialist scarcity. Hiring 80 production-ready AI specialists in a competitive market is a major execution hurdle.
Valliance's bet is that enterprises are sufficiently frustrated with the current model to endure this friction. The next twelve months will be about proving the model can work repeatedly beyond the first three clients.