Ahead of the growing convergence of AI, athlete intelligence, and personalised sports learning, iSportConnect’s Taruka Srivastav spoke with str8bat Co-founder & CEO Gagan Daga about the company’s vision for performance intelligence, the evolution of athlete monetisation, AI-driven coaching, and the future of sports technology. From the KL Rahul x str8bat collaboration to grassroots adoption, global expansion, and the rise of athlete knowledge businesses, Daga shares how connected technologies could reshape how athletes learn, train, and engage with elite sporting expertise.
Most athlete-brand partnerships stop at endorsements. With KLR1 x str8bat, you are effectively turning KL Rahul’s batting knowledge into a scalable digital product. Was this always the long-term vision behind str8bat?
Absolutely. From day one, the vision was never to build a hardware company or an endorsement-led sports brand. The larger vision was to build a performance intelligence platform for human motion in sport.
What we realised very early was that elite athletes carry an enormous amount of tacit intelligence, timing, rhythm, preparation, decision-making, shot construction, pressure management, but historically that knowledge has not been scalable. It remained locked inside dressing rooms, academies, or one-to-one coaching environments.
Technology and AI are finally allowing that gap to close. With KL Rahul, we are not creating another celebrity association. We are building a system where one of the world’s best batters can effectively influence and guide millions of learning journeys through data and AI. That is fundamentally different from advertising.
The larger idea is this: every player should not just watch elite athletes, they should be able to learn from them contextually, based on their own game. That is where sport is heading globally, from content consumption to personalised performance intelligence.
KL Rahul’s batting philosophy, preparation mindset and technical understanding become far more powerful when combined with str8bat powered real player data and GenAI-driven interpretation. That creates a living, scalable knowledge system rather than static coaching content.
And this is only the beginning.
How does the GenAI layer actually work in practice? Can a young cricketer in Lucknow or Johannesburg genuinely receive coaching insights that reflect KL Rahul’s approach to shot selection, tempo-building and preparation based on their own performance data?
Yes and that is precisely the problem we are trying to solve. Traditionally, coaching has largely been generic. Two players with completely different batting patterns often receive the same advice because coaches simply cannot process large volumes of motion data continuously for every player. str8bat is changing that.
Our bat sensor captures real batting intelligence metrics like bat speed, swing path, timing efficiency, impact quality, control, shot consistency and intent patterns. The real breakthrough happens when that data is contextualised through AI and elite cricket intelligence.
The GenAI layer interprets a player’s performance patterns and will convert them into personalised learning feedback inspired by KL Rahul’s approach to batting, how he builds an innings, manages tempo, approaches preparation, constructs shots and adapts under pressure. So a young player in Lucknow, Johannesburg or Melbourne will not receive generic coaching tips. They will receive contextual guidance based on their own game. That is a very important distinction.
We believe the future of sports learning is not mass instruction. It is hyper-personalised performance intelligence. And over time, this becomes even more powerful because the system continuously learns from player progression patterns.
From a business perspective, do you see this as the beginning of a new athlete monetisation model — where intellectual property and methodology become more valuable than advertising inventory?
I would think so! Historically, athlete monetisation has been heavily dependent on advertising inventory, endorsements, campaigns, appearances and sponsorship visibility.
But the deeper and more durable value of an athlete lies in their expertise, methodology and performance intelligence. What AI and connected sports technologies now enable is the ability to convert elite sporting knowledge into scalable digital intellectual property. That changes the economics completely.
An athlete is no longer just a face for a campaign. They can become the foundation of an interactive learning ecosystem that continuously creates value for players globally. I think over the next decade, we will see the emergence of athlete knowledge businesses at scale where expertise becomes a long-term digital asset rather than short-term media inventory. And importantly, this is not limited to cricket. This model can extend across sports globally.
Indian sports-tech startups often struggle with consumer adoption because grassroots sports infrastructure is still fragmented. What helped str8bat build trust among both professional teams and everyday players?
The biggest reason is that we focused on solving a real player problem rather than building technology for the sake of technology. Players fundamentally want to under their own game and improve. Coaches want clarity. Parents want measurable progression. We built around that.
The second thing was simplicity. str8bat works directly on the bat without altering the balance/weight of it. There are no cameras, markers or complicated setups. A player can train naturally and instantly receive objective feedback. That matters enormously in grassroots environments.
The third factor was credibility through outcomes. When elite ecosystems like Rajasthan Royals and Cricket Australia started using the technology, it validated that this was not just another sports gadget, it was serious performance infrastructure.
But interestingly, what helped us most was that amateur players also immediately understood the value. For the first time, they could measure aspects of batting that were previously invisible, timing quality, control, bat flow, consistency. That creates trust because performance becomes objective instead of purely opinion-driven.
You’ve partnered with organizations like Cricket Australia and Rajasthan Royals. How important is institutional validation for an Indian sports-tech company when expanding globally, especially in markets like Australia, the UK and South Africa?
Institutional validation is extremely important in sports because high-performance ecosystems are naturally conservative. Teams and coaches do not adopt technologies unless they genuinely improve player understanding or outcomes.
Partnerships with organizations like Cricket Australia and Rajasthan Royals helped demonstrate that the technology works at the elite level, not just as a consumer product. But beyond credibility, these partnerships also accelerated learning for us.
Working with high-performance environments exposes you to deeper questions around biomechanics, player adaptation, workload, skill repeatability and decision-making under pressure. That pushes the platform forward significantly faster. Over time, we believe India can produce globally respected sports technology companies, just like it has produced globally respected software companies.
Sport is becoming increasingly data-driven and intelligence-led. That creates a huge opportunity for Indian innovation.
There’s increasing conversation around AI replacing traditional coaching. Do you see platforms like str8bat as a supplement to human coaching, or could AI-driven personalised learning fundamentally change cricket coaching economics over the next decade?
Cricket is ultimately a deeply human sport. Coaches do far more than transfer technical information, they understand emotions, confidence, mindset, pressure and personality. AI will not replace that.
What AI can do is dramatically improve the quality, accessibility and personalisation of learning.
Today, high-quality personalised coaching is available only to a very small percentage of players globally. Most young cricketers still operate with limited feedback loops. AI changes that equation. Platforms like str8bat can provide continuous objective insight at scale, helping players understand timing, control, bat speed, consistency, decision-making patterns and progression trends in a far more measurable way.
So I see AI as an intelligence layer that empowers coaches rather than replaces them. But yes, I do believe it will fundamentally change coaching methodology over the years because personalised learning will become significantly more scalable and accessible than it has ever been before. The larger mission is democratisation of elite learning.
The Indian sports startup ecosystem has evolved rapidly after the IPL and the rise of sports consumption platforms. Where do you believe the next big opportunities lie, performance analytics, fan engagement, commerce, gaming, grassroots development, or creator-led sports businesses?
I think the biggest long-term opportunity lies in performance intelligence and personalised sports learning. We are moving from passive sports consumption to interactive sports participation.
AI-led coaching, motion analytics, connected equipment and athlete intelligence platforms will become massive categories globally. I also believe athlete-led creator and knowledge businesses will emerge strongly. Fans increasingly want access to how elite athletes think, train and prepare, not just how they perform on match day. Even during live matches, fans no longer just want outcomes, they want deeper context around motion, intent, timing, pressure and execution. Every ball is an event, every movement tells a story, and increasingly that storytelling will be powered by real performance data and motion intelligence.
At the grassroots level, there is still enormous untapped opportunity because millions of young athletes lack access to structured development systems. Technology can bridge that gap at scale.
And over the next decade, the companies that win in sports-tech will not just build apps or devices they will build ecosystems around human performance