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Reading: Tangam Systems sees rising demand for reliable AI-powered casino analytics
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GGRAsia > Newsletter > Newsletter 3 > Tangam Systems sees rising demand for reliable AI-powered casino analytics
HeadlinesIndustry TalkLatest NewsNewsletterNewsletter 3

Tangam Systems sees rising demand for reliable AI-powered casino analytics

Newsdesk Published May 21, 2026
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6 Min Read

Artificial intelligence (AI) is rapidly reshaping casino operations, but for operators in a heavily regulated industry, the challenge is balancing innovation with trust and reliable outcomes, says Maulin Gandhi, president of Tangam Systems.

Tangam is known for technology such as TYM (Table Games Yield Management) and SODA (Slot Optimisation & Data Analytics).

TYM is described as assisting casino operators in maximising yield by real-time optimisation of table spreads, game mix, pricing, and labour allocation.

SODA is said to help increase slot revenue and player engagement by delivering automated recommendations on slot placement, game mix, and patron reinvestment.

Mr Gandhi said in an interview with GGRAsia that the firm’s new product – previously known as SODA Plus, and now evolving into what he described as a broader “casino performance platform” – has gained strong traction globally as operators seek a more unified understanding of player behaviour across gaming products.

“The customer doesn’t discriminate between a table game, an ETG [electronic table game] or a slot machine,” Mr Gandhi said. “Ultimately, it’s the customers who drive the revenue,” he stated, speaking on the sidelines of Global Gaming Expo (G2E) Asia 2026, a trade show and conference that was held in Macau in mid-May.

According to the Tangam president, the original goal of SODA Plus was to combine traditionally fragmented gaming data sources, including table games, slot machines, ETGs, and customer information, into a single operational view. That integration, he said, has now become the foundation for deploying artificial intelligence and large language models across casino analytics.

“The large language models now actually have a much better” efficacy in relation to “the underlying data to turbocharge the kind of analysis that you can run,” he explained.

Mr Gandhi said the new platform, which he described as a product that provides a “holistic view” of an operator’s “entire gaming portfolio”, is already deployed across multiple jurisdictions: the United States; Europe, including the United Kingdom and Greece; a number of markets in Asia; and in Australia.

“The initial feedback has been overwhelmingly positive. They ask us: ‘Why didn’t you do this 10 years ago?’,” he stated.

Quick ramp-up

Tangam’s customer footprint is also expanding quickly. Mr Gandhi said the firm expects to surpass the 300-venue mark in terms of installation of its products by “July or August this year”. That compares with approximately 200 venues cited in October last year.

While early growth came primarily from major casino brands and integrated resort operators, Tangam is now seeing increased adoption among mid-sized casino groups operating multiple properties.

“They want a centralised view of all their operations,” the executive explained, describing this segment as one of the company’s fastest-growing customer categories.

Discussing the growing role of AI in casino management and the accompanying concerns over data privacy, intellectual property protection and reliability of AI-generated insights.

Mr Gandhi (pictured above) stressed that casino operators remain cautious about exposing sensitive operational data to public large language models (LLMs). In his view, unrestricted use of generative AI tools could potentially compromise proprietary information, if not safeguards are properly implemented.

“Their intellectual property is their data,” he said. “Sending their data to a LLM without any guardrails basically means losing your intellectual property.”

He added: “Our goal is to ensure you get the benefits without the risks of losing control over the data, but with the guarantee of having an output that is trustworthy.”

To address this concern, Tangam applies an application layer between casino databases and LLMs, to ensure that such data is not directly exposed to external AI systems. “The LLM only understands the structure and context of the data,” Mr Gandhi explained. 

At the same time, he warned that operators should remain cautious about over-relying on AI-generated output, particularly as the technology continues to evolve rapidly.

“There is still a lot of hallucination that happens,” he stated, referring to inaccurate or fabricated AI responses. “Even if it’s wrong, it might come across as very confident.”

Mr Gandhi compared today’s AI systems to a junior analyst whose work still requires human oversight and validation. “You have to question the output,” he said. “You can’t just take it for granted.”

Despite the rapid acceleration of AI adoption, the executive said Tangam’s priority remained ensuring that any technology introduced to casino operators is “reliable and trustworthy”.

“We’ve built our brand around being trusted advisors and trusted partners,” he added. “We want to make sure that anything we bring to the industry has been properly vetted and delivers best-in-class analytics and optimisation.”

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