As AI adoption accelerates, so do the risks that come with it, from synthetic identities to increasingly convincing AI-generated documents. For operators, the challenge is no longer just efficiency, but governance, compliance, and trust in the systems they rely on. In this Q&A, Warren Russell, CEO at eyeDP, explores how the company is redefining document intelligence to address AI-driven fraud, while helping businesses navigate the growing complexity of risk, regulation, and responsible AI adoption.
Q: eyeDP is often mentioned in the context of document verification. How do you define your positioning today?
A: Traditionally, document verification has been about checking whether a single file is valid, and using templates to validate the structure. But risk doesn’t sit neatly within one document or a template library. It often appears in the gaps.
What we focus on is understanding documents in context, across formats, languages, and sources, and connecting the information they contain to identify what doesn’t add up. 
Our AI-powered Intelligent Document Processing (IDP) goes beyond ID checks to analyse any document type, format, or language, applying real-time risk assessment, fraud detection, and affordability intelligence across a player’s entire document history. This enables operators to move from reactive compliance to proactive risk management.
Q: What’s driving the need for this shift beyond traditional verification?
A: The nature of fraud has changed.
We’re seeing more synthetic identities, fabricated documents, and AI-generated content that can appear completely consistent on the surface. A document can pass validation and still be part of a broader issue.
That’s why treating documents in isolation is becoming less effective. The real challenge is understanding how everything fits together, not just ticking a box to say “I checked their ID”
Q: Is the industry adapting quickly enough to these changes?
A: Progress has been uneven.
AI is widely used in areas like personalisation and marketing, but less so in core operational functions like compliance and fraud detection. These areas are harder to modernise, but they’re also where the risk sits.
As fraud becomes more sophisticated, the limitations of fragmented systems and manual processes become more obvious.
Our reactive agility significantly reduces false positives and manual overheads.
Our operator clients benefit from a system that not only flags high-risk accounts immediately but also refines accuracy through continuous machine learning, improving performance over time.
Q: What are the biggest operational challenges your clients are facing today?
A: Many are still dealing with a mix of manual review and disconnected systems.
That slows onboarding, increases cost, and introduces inconsistency. At the same time, fraud is becoming more difficult to detect using traditional methods.
There’s also increasing regulatory pressure, which means businesses need to be both fast and accurate, and that’s not always achievable without better automation and visibility.
Q: How does eyeDP approach these challenges in practice?
A: The focus is on automating the full document lifecycle, not just one step.
eyeDP approaches this by focusing on the whole customer journey, not just one part of the process. The platform pulls together data from multiple documents, checks it, and adds context so teams can see how everything connects, rather than reviewing files one by one. That gives a clearer and more complete picture of each case.
In practice, it helps automate things like document verification, risk assessments, and due diligence, while still supporting compliance with requirements such as AML and responsible gambling. The shift is really about moving away from isolated checks to a more connected view, which helps teams make decisions faster and with more confidence.
Q: eyeDP mentions detecting fraud that humans might miss. How should that be understood?
A: It’s about scale and perspective.
Manual review is limited by time and volume. When you’re dealing with large datasets, it becomes difficult to consistently identify patterns or subtle inconsistencies.
By analysing relationships across documents and cross-referencing data, you can highlight signals that wouldn’t be obvious otherwise. It helps teams focus their attention where it’s actually needed.
Q: How does the platform fit into existing workflows?
A: Most organisations don’t want to replace their systems, they want to improve them.
eyeDP is designed to integrate into existing onboarding and compliance workflows, either through APIs or no-code/low-code options. It acts as an additional layer of intelligence rather than a separate process.
The goal is to unify what are often fragmented checks into a more coherent view.
Q: eyeDP also refers to replicating open banking insights. What does that involve?
A: Open banking is useful, but it’s not always available or accepted.
In those cases, documents like bank statements, tax returns and payslips still contain valuable information. By analysing those documents, it’s possible to extract similar insights and support decision-making without relying on direct integrations.
It ensures continuity in how businesses assess risk.
Q: What’s the broader takeaway for operators navigating this landscape?
A: The shift is from verification to understanding, from process driven compliance to evidence driven compliance.
As fraud becomes more complex, businesses need to move beyond isolated checks and develop a more complete view of the data they rely on.
When you can see how everything connects, you can make faster decisions without increasing risk.
Q: eyeDP recently closed a late Seed round. What does this milestone enable for the business?
A: It gives us the space and ability to really execute on what we’ve been building towards. The round, backed by a close group of experienced angel investors and industry figures, means we can stay focused on the next phase without distraction.
Over the next 12 months, that’s about expanding our product, improving accuracy, and continuing to move towards fully automated document processing. We’re also growing the team, which is important as the platform scales and the problems we’re solving become more complex.
