By Tatiana Martins, journalist at G&M News.
Your firm is building a B2B SaaS platform focused on affiliate marketing. What gaps or operational challenges in the current affiliate ecosystem led you to create the company, and what did you want to approach differently from existing solutions?
The biggest gap we saw was that affiliate software was still mostly built around tracking, while the actual job had become much bigger. Affiliate teams are analyzing performance, managing risk, improving conversion, handling finances and growing partnerships, often across several tools and spreadsheets. That’s what we wanted to change with iGsuite. Tracking is the foundation, but around it we’ve built BI, CRO, Risk & Fraud Management, accounting and Affiliate Gamification. For us, the shift is simple: affiliate software shouldn’t just tell you what happened. It should help you understand where you make money, where you lose it, and what to do next. That’s why we see iGsuite not just as software, but as revenue infrastructure.
You are responsible for product strategy, software architecture and technology direction at iGsuite. How do you balance the need for a flexible platform that can serve different operators and affiliate businesses with the necessity to maintain scalability, reliability, and operational control?
Every operator works slightly different, so flexibility matters. If you build every client their own version of the product, you don’t really have a scalable product anymore. We try to understand the actual business need behind a request and solve it in a way that can work across clients through configuration rather than endless custom development. The balance we aim for is simple: flexible for the customer, but not chaotic underneath. We want one strong product that can keep evolving with our clients and the industry.
Affiliate management increasingly involves large volumes of data across tracking, performance, payments, fraud prevention, and accounting. How is the company approaching data and business intelligence to help operators turn this information into practical decisions?
There’s already more than enough data in iGaming. The problem is that people still spend far too much time trying to understand what it actually means. With Newton, our BI layer, we connect affiliate, player and financial data to make the important things obvious: what changed, where money is being lost and where there’s an opportunity. For us, BI isn’t there to give you more dashboards. It’s there to help you make more profitable decisions. The goal is simple: less time building reports, more time making decisions.
Fraud and compliance are becoming increasingly important in affiliate operations. From a technology perspective, what are the main challenges involved in identifying suspicious activity while keeping legitimate affiliates and partners from being negatively affected?
The tricky part with fraud is that ‘suspicious’ doesn’t always mean fraudulent. CPA abuse, bonus abuse, stimulated CPA and traffic mixing all behave differently, so we look at them through different detection lenses rather than trying to solve everything with one generic rule. We also separate fraud from risk. A deal might be completely legitimate but still have a very low probability of paying back within a reasonable timeframe. The goal isn’t to flag everything unusual. It’s to catch real exposure without punishing good affiliates in the process. Wherever possible, we want operators to understand why something was flagged, not just receive a black-box yes or no.
You are also applying AI-assisted product engineering to accelerate development. Beyond speeding up coding and product delivery, where do you see AI creating the greatest opportunities for affiliate marketing platforms and the companies that use them?
Coding faster is useful, but I think AI gets much more interesting when it starts helping people think faster. iGaming affiliate businesses generate huge amounts of data, but nobody has time to analyze all of it continuously. AI can surface anomalies and explain why performance changed and point you towards the things actually worth investigating. Eventually, instead of digging through reports, an affiliate manager should be able to ask: “Why did our margin drop this month?” and get a meaningful answer based on the underlying data. For me, that’s the exciting part: not replacing the affiliate manager but giving them a much smarter way of working. At the end, is important to remember that tracking becomes revenue infrastructure, data becomes decisions, and the platform helps operators analyze, optimize, and protect the economics behind affiliate acquisition.