Quick Custom Intelligence (QCI) has announced the expansion of its private AI initiative designed to help tribal gaming organizations adopt generative AI while maintaining ownership and control of their operational knowledge.

QCI’s framework combines privately deployable large language model (LLM) technology with support for emerging Model Context Protocol (MCP) standards, enabling tribal enterprises to integrate generative AI into business operations without exposing sensitive institutional knowledge to public AI ecosystems. The initiative comes as concerns around AI governance, knowledge leakage, and ownership of generative data continue to grow across the gaming and hospitality industries.

“Generative AI can now learn from the operational knowledge inside organizations. The critical question for tribal enterprises is whether that knowledge remains sovereign,” said Andrew Cardno, Co-Founder and CTO of QCI.

QCI’s private AI approach is designed to help tribal nations leverage AI productivity gains while protecting governance practices, operational strategy, and enterprise intelligence from external model training and knowledge replication.

“Tribal enterprises should benefit from AI without surrendering the operational blueprint that makes them unique,” Cardno added.

Quick Custom Intelligence (QCI) a leading provider of casino operational intelligence software, announced the launch of QCI Metrics, a new anonymized data-sharing program that enables gaming and hospitality operators to benchmark performance using yesterday’s operating data—providing timely, actionable insights without exposing customer, financial, or personally identifiable information. This innovative solution extends beyond gaming machine ranking into host performance standardization.

Available through the Chatalytics.com portal and integrated into the QCI Platform, QCI Metrics transforms operational data—including game performance and host effectiveness—into standardized performance indexes.

While traditional benchmarking solutions rely on limited datasets or delayed reporting cycles, QCI Metrics delivers insights based on yesterday’s data—giving operators a timely, continuously updated view of how they are performing against peers across both gaming and player development.

All data shared in QCI Metrics is:

• Aggregated and normalized

• De-identified

• Abstracted at the property level using internal IDs

No transaction-level, player-level, or campaign-level data is ever shared.

“QCI Metrics gives operators the ability to see how they stack up against peers across player development and gaming in near-time, without compromising privacy. It’s a practical, secure way to unlock industry-wide insights,” said Andrew Cardno, Co-Founder and CTO of QCI.

QCI Metrics is designed to help operators quickly identify performance gaps, respond faster to trends, and adopt proven strategies in a highly competitive environment.