How FanCode Delivered 1080p Quality to 160 Million Sports Fans Without Increasing Data Costs

FanCode is India’s leading digital sports platform, serving more than 160 million sports enthusiasts with live and on-demand content across Formula 1, cricket, football, golf, MotoGP, and more. Launched in 2019, the platform operates under Dream Sports — the country’s largest sports technology company and parent of Dream11.

FanCode’s audience is mobile-first, spread across urban and rural India, and intensely passionate about sport. That passion, however, coexists with a very practical constraint: data costs. For millions of fans, every gigabyte consumed matters.

India’s mobile streaming market presents a paradox that keeps engineering teams up at night: audiences demand premium video quality, yet network conditions and data costs vary dramatically from user to user, city to city, and carrier to carrier.

Visionular’s AuroraCloud platform combines standards-compliant, AI-driven encoding with cloud-native scalability. Rather than applying uniform compression across a video stream, it analyzes each frame in real time, identifying the visual elements that matter most to the human eye and allocating bits accordingly.

• Frame-level AI analysis identifies fast-motion scenes, fine detail (ball trajectory, player positioning), and high-contrast moments, precisely where traditional encoders waste bits or lose quality.
• Content-adaptive encoding allocates bitrate intelligently: more where it matters, less where it doesn’t, without sacrificing perceptual quality.
• Standards-compliant output means zero changes to FanCode’s existing player infrastructure, CDN, or delivery pipeline – the solution plugged in seamlessly.
• Cloud-native architecture scales elastically with demand spikes – live sporting events, playoff surges, tournament finals – without manual intervention.

AuroraCloud does not require viewers to do anything differently. There is no new app, no settings change, no special device. The better quality and lower data usage happen automatically at the encoding layer — before the video ever reaches the user’s screen.

Read similar case studies with ShareChat, Huya, Hudl, and Stage.in.

Contact us to experience the power of AI-driven video compression in your streaming business.