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Raphie Co-Founder Talks iGaming Support with iGamingExpert

Justin Heath, Co-Founder of Raphie, has talked to industry media iGamingExpert to discuss why effective AI support needs to combine live context, automation and human oversight – a conversation that aligns with the question operators are asking right now: whether AI can work accurately inside a live operating environment.
The interview traces Raphie's path from Conduet, founded in 2019 to deliver player support for sportsbook and iGaming operators, through to the AI platform built on that same operational foundation.
Heath points to a distinction he sees as central: resolution versus response. A conversation can look fluent and technically closed while the underlying issue stays unresolved. In moments involving payments, account access or responsible gaming, that gap carries real consequences for service quality and player trust.
Raphie's AI Support Platform is built on more than one million real iGaming interactions, and can resolve 75%+ of tickets in live production, with player satisfaction staying above 90%.
Operationally, Raphie connects into an operator's existing PAM, CRM and ticketing environments, using live player context and operator-approved rules to act within those workflows. Guardrails and responsible gaming logic sit around the AI, so cases requiring judgement move to trained people – escalation built into the model, not bolted on as a fallback.
On rollout, Heath describes a contained approach: a typical proof of concept runs one defined use case over ten weeks, giving operators a controlled way to test performance before deciding where to extend it. SOC 2 Type II and GDPR-aligned controls run alongside, covering encrypted data flows, PII redaction and auditability.
Read the full interview on iGaming Expert: From Conduet to Raphie: iGaming support meets agentic AI
Want to see how this plays out for your own operation? Talk to us.
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Raphie Co-Founder Talks iGaming Support with iGamingExpert
Raphie Co-Founder Justin Heath tells iGamingExpert why AI support needs live context, automation and human oversight to actually resolve issues.
