Chaim Heber, Co-Founder & CEO of Cevro.ai, is building AI agents for iGaming operators that move beyond scripted chatbot responses into contextual player support. The company focuses on agents that can understand player history, access back-office systems, and take defined actions across areas such as withdrawals, bonuses, KYC, and communication preferences.
In this Casinorank interview, Heber examines why player interaction is becoming a strategic layer in iGaming rather than a support function alone. He discusses the shift from deflection to resolution, the role of deep system integration, and how AI agents could bring support, CRM, compliance, and retention into a single continuous player conversation.
From your perspective as a founder, what was the key realization that led you to focus on AI-driven player interaction as the next critical layer in iGaming?
Chaim Heber: The key realization came from understanding that the majority of iGaming operators were losing players silently and consistently, through customer support friction. A withdrawal that took too long to process, a bonus question that went unanswered for hours. A KYC request that felt cold and robotic.
Support is the most frequent touchpoint operators had with their players, and it is being systematically underinvested in. The realization was simple: if you fix support, you analyze player engagement better. And the new developments around AI make it possible to fix it at scale.
Your platform goes beyond automation with “AI agents with memory and context”. How do they differ from traditional iGaming chatbots?
Chaim Heber: Chatbots answer questions, whereas AI agents solve problems. The difference sounds semantic but it’s everything in practice. A chatbot reads keywords and returns a script. An AI agent understands what the player is trying to achieve, holds context across the conversation, knows that this player is a VIP who deposited three hours ago and is now frustrated – and makes a decision accordingly.
AI agents are able to access a backoffice, retrieve information and take actions. The chatbot era was about deflection. What we’re building is about real resolution that boosts player satisfaction. They are genuinely different products.
How is Cevro AI unifying support, CRM, and player engagement into a single interaction layer for iGaming operators?
Chaim Heber: For as long as I can remember, customer support in iGaming has been treated as a cost centre, something to be managed down, outsourced, or automated away. It sat completely separate from CRM, which was seen as the “real” retention function. Two teams, two budgets, two conversations with the same player who had no idea the left hand didn’t know what the right hand was doing.
What we’re seeing with operators who’ve been on Cevro for a while is that this separation starts to dissolve naturally. When an agent knows a player’s full history, their tier, their last interaction, their open bonus — and can act on all of it in real time — it stops being a support conversation and starts being a relationship. Players come back not just with problems, but to check on promotions, ask about their account, engage. The support channel becomes a communication channel. That’s not a feature we built. It’s what happens when you stop treating CS as a cost and start treating it as the most frequent, highest-intent touchpoint in your entire player relationship.
You’ve introduced “VIP-level support for every player.” What made this impossible before, and what makes it scalable now?
Chaim Heber: The economics were the constraint. A VIP manager for every player is obviously impossible to achieve at scale. What changed is that AI can now carry the full context of a player relationship without fatigue, inconsistency, or shift changes.
The personalization that used to require a human who “knew” the player can now be implemented at the start of every single conversation, for every player, simultaneously. That’s a genuinely new capability. It wasn’t possible three years ago.
With partnerships like EveryMatrix and Vegangster, how important is deep system integration to making AI agents truly valuable?
Chaim Heber: It’s not optional, it’s the whole game. An AI agent that can’t actually touch your systems is just a very expensive FAQ. The moment you connect the agent to your payments stack, your bonus engine, your KYC provider – it stops being a chatbot and starts being a real agent.
It can check a withdrawal status in real time, trigger a KYC reverification, unlock a free spin. That’s what resolution looks like. Ready-made integrations with PAMs and several other platforms aren’t a nice-to-have on our roadmap. They’re what makes the product work.
AI in iGaming raises compliance concerns around bonuses, KYC, and responsible gaming. How do you keep autonomous agents within strict regulatory frameworks?
Chaim Heber: This is where iGaming-native AI has a real edge over general-purpose tools. We built the concept of AI Procedures – essentially structured decision logic that defines exactly how an agent behaves in regulated scenarios.
Bonus abuse handling, responsible gambling flags, KYC workflows – these aren’t left to the model to interpret freely. The agent follows a defined procedure with guardrails, escalation triggers, and audit trails. Compliance isn’t a layer we added on top. It’s baked into how the agent reasons and acts.
One of the most interesting aspects of your product is that AI agents can actually take action. How does this shift the role of AI from assistant to operator?
Chaim Heber: That’s exactly the right framing. An assistant tells you what to do. An operator does it. When our agents process a withdrawal, reverse a transaction flag, or update a player’s communication preferences – they’re not assisting a human agent, they’re executing.
The human is freed up for the edge cases that genuinely need judgment. That shift changes the economics of support completely, but more importantly it changes the player experience. Resolution in seconds instead of minutes or hours. That’s what players actually want.
Cevro AI emphasizes “empathy at scale.” How do you design automation that still feels human?
Chaim Heber: You start by being honest that you’re not engineering empathy – you’re engineering the conditions for it. Understanding context. Recognizing frustration signals in how a player writes. Knowing that a player who’s had three failed withdrawals this week needs a different tone than someone asking about wagering requirements for the first time.
The model handles language. We handle the logic that tells it who it’s talking to and what that player’s situation actually is. When those come together, players feel understood.
Looking ahead, do you see player interaction evolving into a single intelligent interface where support, marketing, and engagement all happen in one continuous conversation?
Chaim Heber: Yes, and I think the operators who get there first will have a structural advantage that’s hard to close. Right now, support and CRM are separate stacks with separate teams and separate conversations with the same player. That’s inefficient and, frankly, it’s a worse experience for the player.
The natural endpoint is a single interaction layer that knows the full player relationship and can act across all of it. Support. Retention. Reactivation. All in one continuous conversation. We’re not fully there yet, but every deployment we do gets us closer to that picture.
With a background in digital media and a keen eye for emerging technologies, Ronaldo bridges the gap between players and platforms through clear, insightful reporting to the iGaming industry.
