EveryMatrix CTO Pablo Jensen: AI already improves Bonus Guardian and game recommendations
EveryMatrix's CTO says AI is already measured inside Bonus Guardian and game recommendations, with a human always making the final call.
Key takeaways
- 1EveryMatrix runs AI on two tracks: inside operator-facing products and inside internal workflows such as engineering, legal, commercial and finance.
- 2AI already feeds Bonus Guardian, game recommendations, bonus-abuse detection, personalisation and player protection, with results tracked through metrics like stay on page and game rounds.
- 3Pablo Jensen says every AI-assisted decision, from Bonus Guardian flags to Bet Builder suggestions, still ends with a human making the final call.
EveryMatrix published an interview on 2025-07-18 in which Chief Technology Officer Pablo Jensen set out how the B2B platform provider is using artificial intelligence across its products and internal operations, speaking to HIPTHER during the EveryMatrix Media Event in Copenhagen.
We always have this human in the loop.
Two tracks for AI
Jensen described EveryMatrix’s approach as running on two tracks. The first uses AI within the product line sold to operators; the second applies AI to internal processes to make teams work more efficiently. Internally, that includes generative AI tools across engineering as well as legal, commercial and finance teams. On the product side, machine learning is applied across EveryMatrix’s data platform to bonus abuse detection, game recommendations, personalisation and player protection.
Jensen also pointed to data sovereignty as a priority, saying client data stays within dedicated environments, alongside ongoing work on local language models and controlled data usage.
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Where AI is already measured
According to Jensen, EveryMatrix tracks the performance of AI-driven functionality in areas such as Bonus Guardian and game recommendations, using metrics including stay on page and game rounds. He said the company is seeing “good results” from that tracking. The same behavioural-data approach is applied to fraud and bonus-abuse detection, and to system monitoring, where Jensen said AI can help flag potential technical incidents before they escalate.
Human in the loop
In Bonus Guardian, AI surfaces potential issues through a dashboard, but the final decision on what action to take stays with a person, Jensen said. The same principle applies internally: code is not moved into production without human oversight. In Bet Builder, AI can generate or recommend bet combinations, but Jensen said the player still decides what to add to their bet slip.
Jensen also raised scale as a challenge, since EveryMatrix deploys across dozens of regulated markets and hundreds of clients, relying on hosting and DevOps infrastructure to manage updates while keeping client environments separated.
Looking toward 2030
Asked about the future, Jensen said one of the biggest opportunities is automating how platforms are configured for operators, a process that today combines manual work on regulation with each operator’s commercial objectives. He said data security will become more important still, predicting “many more closed environments client to client, where there is AI working on the data for that specific client.” For EveryMatrix, Jensen said, that means combining smarter technology with stronger data controls, measurable outcomes and human oversight.
BackgroundAI Fraud and Integrity Detection in Gambling: Match-Fixing, Bonus Abuse, AMLHow AI Is Used in Sports Betting: Odds, Assistants, Streams and IntegrityBonus Guardian (EveryMatrix)
