ThinkingDataAI launches Agentic Engine with AI agents tracking growth on a company’s own infrastructure
ThinkingData Information Technology Pte. Ltd. today announced the launch of the Agentic Engine, an autonomous growth platform for consumer and gaming businesses that uses artificial intelligence to track data, experiment and develop campaigns.
Modern companies spend hundreds of thousands of dollars on campaigns developing events to sell services that produce customer data. While they run, teams can wait weeks for that data to collate and revenue can leak into that gap before a company can act on it.
ThinkingData believes pricing tied to that event and monthly tracked users could let a company react more nimbly if measurements worked off real-time tracking, prediction, engagement, and experimentation working together. This is what the company said its Agentic Engine helps prevent common bottlenecks.
“Everyone’s models are smart enough. That stopped being the problem a while ago,” said co-founder Chris Han. “What customers keep asking is whether they can trust an agent to touch live revenue, and that’s the whole game.”
The engine runs on the customer’s own infrastructure and uses existing models, including self-hosted, on-premises and private cloud deployments.
The company said analytics agents from competing platforms will discover a finding and hand it back to a person. The Agentic Engine differentiates itself by taking insights the rest of the way with an updated tracking plan, a rebuilt audience segment or a redesigned campaign. ThinkingAI calls this category agentic growth.
To build the Engine, ThinkingAI used gaming workloads as training foundations where retention and monetization can change from moment to moment. The company said it has been working with behavioral data for more than 1,500 enterprises and 8,000 applications, including Sega, Krafton, Habby and Century Games.
“Cost savings are the easy part,” said Vice President of Marketing Brandon Nader. “The number I care about is how long it takes to get from noticing something in the data to changing something in the product.”
Nader added that most teams measure that in weeks, noting that this is where the money goes. ThinkingAI wants to change that so teams can react faster and get what they need. The company added that data-tracking implementation drops from weeks to hours and that junior operators get the same answers senior analysts would have produced.
The company has taken what it has learned and battle-tested from within the gaming industry, where margins are thin and reaction time is short, and is now applying it to consumer companies outside gaming.
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