Gaming Intelligence: Real-Time Data With AI Boost Could Be the New Frontier Game State Labs, a Bangalore-based AI infrastructure company for gaming, has raised USD 2 million in a seed round co-led by PeerCapital and Neon Fund.

Whether it's a prominent firm like EA or a smaller one, firms leverage the data intelligence to strategically drive business outcomes. Intelligence provides insights into how well users receive the game, churn probabilities, and most importantly, personalised in-game content and monetisation opportunities.

While the conventional systems have worked, with AI and better data management, can data intelligence for gaming be better?

Bengaluru-based Game State Labs, which on Thursday announced raising USD 2 million in a seed round co-led by PeerCapital and Neon Fund, is building the data-plane of intelligence for the global gaming industry.

The company says its technology enables gaming studios to develop a deeper understanding of player behaviour with minimal effort. It also aims to leverage its data-plane to deliver accurate predictive analytics and deliver hyper-personalization use cases that adapt to each individual player.

"What is happening in the gaming industry, specifically in the mobile gaming vertical is that the reliance on third-party data is slowly reducing whereas customer acquisition costs have increased significantly in the past few years… so now, just relying on your institutions to take decisions is not enough and at the same time, just relying on high-level data is also not enough. So, one really needs to invest a lot into digging deeper into the available data to better understand player behaviour," Aashbir Bhatia, co-founder of Game State Labs, told Entrepreneur India.

"... basically, a lot of first-party data of player behaviour is getting collected but the technology to use and leverage them effectively to drive values is missing," he added.

Game State Labs also said in a note that the most analytics systems in gaming today treat player behaviour like clicks on a website, capturing surface-level metrics but missing the complex in-game states that define player intent. The company aims to address this through capturing every in-game event with the full player state, processing millions of data points per second, and making them instantly usable by AI models. Subsequently, companies get a system that is continuously learning and adapts to players in real-time.

Diving deeper into the data intelligence for the sector, it's worth noting that conventional metrics, which are also pointed out by Game State Labs, are things like DAU and ARPU. These metrics do tell what is happening but not enough to give detailed insights into why. Therefore it's important for firms to take into account of in-game player state data every action, decision, and contextual event.

"For studios, that means being able to predict which micro-experiences drive retention or frustration, dynamically tune gameplay, and personalize engagement in ways surface metrics never could. The business impact is immense higher lifetime value per player, faster iteration cycles, and a much stronger return on content and live ops investment," Vatsal Bhardwaj, Founder of Jabali AI, explained it to Entrepreneur India.

Real-time analytics or processing will help the firms and studios to act during the moment of friction instead of waiting it out, and eventually better predict the churn.

"Churn prediction is just the beginning. A continuously learning data-plane enables far more transformative use cases: early LTV prediction for smarter user acquisition, real-time matchmaking balance, adaptive difficulty tuning, and fraud detection within milliseconds," Bhardwaj added.

AlphaZegus founder and director Rohit Agarwal tells Entrepreneur India, "We've seen games lift day-7 retention by 8-12% and IAP uptake by 15-20% simply because they could detect friction moments and serve the right offer or difficulty at the right time. That's the real business impact- precision, not averages."

For data intelligence firms or gaming studios, latency is an important factor for in-game personalization.

"Let's take dynamic difficulty adjustment as an example. So, let's say if a player completes level 8 and, uh, then they come on level 9, and at that time, when the player is on level 9, you have to figure out what is the difficulty of level 9 that you want to serve. So, in this case, the system has to see the current state of the player, the history of the player, and at what is the latest action that the player did? Based on that, the system needs to infer what is the right variant that should be served to this player. And the system after inferring that also needs to communicate that back to the game as well. So, latency is very important in this case," Bhatia explained.

Agarwal expresses optimism that the ecosystem is heading toward games that tune themselves around the player.

"In five years, expect: Adaptive difficulty by persona (not just 'easy/medium/hard' but 'failed twice in PvP --- give a winnable match'). Dynamic offers priced to player lifetime, not to catalog. Contextual session goals ('you always leave after 6 minutes --- here's a 5-minute quest') Toxicity-aware lobbies that silently separate bad players. That's all powered by real-time player intelligence- the data layer comes first, the personalisation layer follows," he said.

That said, it's worth highlighting that the global gaming industry is massive in size. It is poised to hit USD 665.77 billion by 2030, according to Fortune Business Insights. As of 2023, the industry was worth USD 281.77 billion. Separately, Niko Partners' India Gamer Behavior and Market Insights report reveals that India will surpass 500 million gamers in 2025 with player spending is forecast to exceed USD 1 billion in 2025. It further says that women now comprise approximately 40 % of gamers in India, up from 22 % five years ago (2020).

With the volume of player data, estimated to be more than 50 terabytes a day, analytics and intelligence firms have access to a gold mine of data, albeit only if it's effectively used.