Anita Rajdev is a co-founder of Valliance, a London-based AI consultancy that charges clients according to the value it delivers rather than the time spent on a project.
A trained management accountant, Rajdev began her career at Andersen Consulting before working with smaller companies to help them scale. At Valliance, she is responsible for finance, treasury, mergers and acquisitions, HR, legal and operations.
During our interview, Rajdev explained how Valliance structures its value-based fees, why companies often underestimate the potential return from AI, and what she has learned from building a finance function without an established playbook.
Valliance charges clients for the value it delivers rather than the time spent on a project. How does that work?
Valliance was created to help clients realize measurable value. We made a commitment that we would not sell time and materials.
Our model is value-based, which means we do not receive the full payment unless we deliver the agreed results. That requires us and the client to define the outcome clearly from the beginning.
Does charging for results make it harder to predict revenue and manage cash flow?
It is much harder than billing for hours. We manage that through the structure of our fees and disciplined forecasting.
We charge a base fee based on our assessment of the risk, our confidence in achieving the result, and what the project will require. The base fee also shows that the client has some skin in the game. We then agree on a value share connected to the result.
I forecast different scenarios, including what happens if we receive all or none of the success fee. Those scenarios provide guardrails when I prepare reports for our investors.
We are also selective about the clients we work with. If a client wants a conventional time-and-materials arrangement, we may not be the right partner for them.
How can finance leaders tell whether an AI investment is delivering real value?
Start by agreeing on the intended outcome before spending begins. Finance leaders should ask whether the completed work mattered, what it cost from end to end and whether the output was good enough to use.
They should also determine whether the investment improved decision-making or helped the business move faster. If you remain focused on those questions, the business case becomes much clearer.
Attribution also needs to be agreed at the beginning. An AI project may involve internal teams and other third parties, so companies must be clear about who contributed to the result. You can only save a dollar once.
What have you learned from building the finances of a new business from the ground up?
The biggest lesson has been unlearning some of the conventional finance practices I encountered in larger organizations. When you inherit a 40-page board report, it may exist simply because that is how the company has always done things.
At Valliance, I can build reporting around real-time decision-making rather than producing reports for the sake of it. I would eventually like us to achieve a real-time close, with information available to everyone every day.
Starting from scratch can be harder because there is no prescribed playbook. However, AI has expanded what a small team can accomplish. I would not have thought it possible for me to manage this many functions with only one part-time colleague a few years ago.
Why did Valliance’s founders decide not to use traditional C-suite titles?
Traditional titles can bring assumptions about hierarchy and how information moves through an organization. AI has started to break down some of those structures.
At Valliance, we are all builders. A CFO title can sometimes place someone into a conventional finance role, but I have always worked across more than finance.
We sometimes use familiar titles externally to help people understand our responsibilities. Internally, however, we want to hold on to a structure that reflects how we actually work.
What is the biggest mistake companies make when calculating the potential return from AI?
Companies often calculate the return by looking at an existing process, estimating how many hours AI could save and treating those hours as the total value.
They should also consider what the team can accomplish with the time it recovers. If employees can complete more work or focus on higher-value activities, the benefit may extend well beyond the initial time saving.
AI is not a silver bullet. Companies may need to address problems with data quality, data ingestion or conflicting information before adding AI. They should start with the problem and work backward rather than assuming AI will fix everything.
What could encourage more women in senior finance roles to start their own businesses?
More visible female leaders would help. When women see someone like them succeeding in a senior role, it becomes easier to believe they can do it too.
It is also important to surround yourself with people who think differently. I have a talented team that values my contribution and gives me a seat at the table.
When you have the right people around you, why not take the opportunity?
What advice would you give someone who wants to build a career in finance or start a business?
Believe in yourself. I was comfortable at EPAM and loved working there, but I have always had a sense of curiosity and a desire to keep moving.
If you are genuinely passionate about entering finance or starting your own business, especially as a woman, you can do it. You can have it all.
Anita Rajdev is a co-founder of Valliance, a London-based AI consultancy that charges clients according to the value it delivers rather than the time spent on a project.
A trained management accountant, Rajdev began her career at Andersen Consulting before working with smaller companies to help them scale. At Valliance, she is responsible for finance, treasury, mergers and acquisitions, HR, legal and operations.
During our interview, Rajdev explained how Valliance structures its value-based fees, why companies often underestimate the potential return from AI, and what she has learned from building a finance function without an established playbook.
