Customer Service Automation
TechD needed to help a multi-state lottery and digital gaming client answer high volumes of highly specific player questions quickly and consistently despite changing rules, promotions, and jurisdiction-specific regulations.
Reported impact
The TechD solution reduced support workload, improved satisfaction, and let the lottery enterprise handle player queries consistently across states and platforms without scaling its human support team at the same rate.
TechD built a virtual-agent solution for the gaming and lottery sector on NeuralSeek, IBM watsonx Assistant, and IBM Cloud so player support could move from manual queue handling to AI-driven self-service. NeuralSeek provides the natural-language layer that combines large language models with the operator’s knowledge base, while watsonx Assistant and IBM Cloud support scalable delivery across lottery and online gaming channels. The assistant answers questions about winnings, promotions, state-specific rules, and other rapidly changing details in seconds, and its analytics and real-time response layer help keep answers consistent even as content changes. Sensitive player data is protected across the multi-state environment, and the same platform can assist multiple lotteries and gaming properties without requiring separate support stacks. By reducing first-line workload and giving players immediate, accurate responses around the clock, the solution improves customer experience and protects revenue for the jurisdictions that depend on those gaming operations.
Player questions arrive from lotteries and online gaming platforms, NeuralSeek and watsonx Assistant interpret the request against the gaming knowledge base, relevant answers are returned in seconds, and support analytics and protected player data keep the system current across jurisdictions and promotions.
“Additionally, the TechD solution protects personally identifiable information (PII)”
“TechD’s virtual agent-based solution design was based on NeuralSeek ... with IBM watsonx Assistant and IBM Cloud.”
“The virtual agent efficiently handled player queries across multiple state lotteries and online gaming platforms”
“players now receive specific answers in a matter of seconds”
“reducing the workload on the customer support team by 40%–60%”
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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