News from LERIS.

LERIS DAY 2026 will take place on Thursday, 15 October 2026 at Hotel Atlantis in Rozdrojovice. The event is intended for our partners and customers, with whom we want to share development results, experience from real operations and the next direction of our solutions in person.

The main programme will focus on the use of AI in casino environments, working with operational data in real time and a new generation of player relationship management tools. We will also present further developments in business intelligence, proprietary hardware, payment processes and the connection between landbased and online environments.

We will place each topic in a practical context. The focus will be on how new technology can make decisions more precise, simplify day-to-day operations and create a more personal player experience while preserving the operator’s rules and responsibilities.

If you have not received an invitation and would like to learn more about our products and technological direction, please contact us. We will be happy to discuss attendance with you.

We have significantly expanded LERIS BI and Data Studio. The new capabilities make it possible to build custom reports, indicators and interactive dashboards over operational, player and financial data. Different periods can be compared in a broader context, while available information can be shaped into views suited to specific roles and operator needs.

The development also includes the ability to work with custom input and calculated data. An organisation can define its own internal indicators and use them across tables, filters, reports and dashboards without requiring separate development for every adjustment.

Our AI agents have also taken a significant step forward. When working with a player, they assess the current context, history and financial relationships with greater precision. They can coordinate individual communication steps more effectively, use available channels and respect individually configured rules and budgets.

We verify new approaches in a controlled mode using real operational data. AI is therefore gradually moving from preparing recommendations towards managed automation whose behaviour remains measurable, traceable and under the operator’s control.

AI AML Manager analyses selected transactions together with the player’s history, the way the account is used and the sequence of previous financial operations. Rather than following one isolated value, it looks for combinations of events that may indicate unusual behaviour, an attempt to misuse the system or a discrepancy that requires review.

The analysis is converted into a clear risk assessment. Suspicious cases are flagged, the main reasons for the assessment are explained and the cases are collected in a dedicated overview. In serious situations, the system can pause a particular type of transaction and refer the case to an authorised member of staff for verification.

The solution combines AI analysis with firmly defined security rules. Operators gain an additional control layer that works continuously, directs attention to genuinely unusual cases and preserves the traceability of the entire decision-making process.

AI AML Manager does not replace the responsibility of qualified staff or the operator’s internal rules. It extends them with the ability to connect relationships across a volume of data that could not be assessed with the same continuity through routine manual checks.

Player DNA brings available data together into a continuously updated picture of player behaviour. It follows long-term activity, changes over time, gaming preferences, deposit behaviour and communication patterns. It also respects valid consent settings and helps identify important changes that would remain hidden when individual data points are viewed separately.

The result is not a fixed category, but a profile that develops with the player. Operators gain a better understanding of the player’s current state, changes in activity and relevant characteristics. This supports more precise decisions about when to communicate, which content to choose and when it is more appropriate not to intervene.

Live Bonusing builds on this context by monitoring events in real time. Within predefined rules, it can respond with an informative or congratulatory message and offer an appropriate immediate bonus action. The decision reflects both the current situation and the player’s long-term profile.

Together, the two modules move personalisation from broad campaigns towards contextual work with an individual player. The operator continues to define the rules, available channels, budgets and safety boundaries within which the automation operates.