Erhan Ciris Explains How 4D Sight Chose the Hardest Broadcast Environment on Earth to Prove Its AI

When Erhan Ciris set out to build 4D Sight, he had a choice. He could start with a controlled, predictable broadcast environment where the variables were manageable and the stakes were low. Or he could go straight into esports.

Ciris picked esports.

Competitive gaming is one of the most demanding live media formats that exists. Camera perspectives shift constantly. The action moves at a pace that makes traditional sports look leisurely by comparison. Visual complexity is extreme. If the technology hesitates for even a fraction of a second, it is immediately visible to millions of viewers.

That is exactly why Ciris started there. He knew that if 4D Sight’s AI could handle the speed and unpredictability of competitive gaming broadcasts, it could handle anything.

What 4D Sight’s Technology Actually Does

At its core, 4D Sight is a real-time perception system built by Erhan Ciris and a team with deep roots in autonomous robotics, UAV navigation, and synthetic aperture radar imaging. These are fields where real-time spatial reasoning is not a feature but a requirement.

4D Sight processes a single live broadcast feed in the cloud and builds a spatial understanding of the environment as it unfolds. The AI interprets the geometry, depth, motion, and lighting of the scene, then inserts photorealistic virtual content directly into the broadcast so that it appears to physically exist within the space.

This is not an overlay. It is not a graphic pasted on top of the action. The content behaves the way a real object would behave in that environment, responding to camera movement, lighting changes, and spatial relationships.

The approach is built on deep learning research that the 4D Sight team began in 2020, and it is protected by U.S. Patent 11,270,517. Everything runs in the cloud with latency measured in milliseconds. There is no need for sensors, on-site hardware, or manual calibration at the venue.

From Esports to the Octagon

After proving 4D Sight’s technology in gaming environments with partners like Riot Games, Ciris expanded into traditional live sports in 2023 through a multi-year partnership with TKO, which includes the UFC and WWE.

The transition brought a different set of challenges. Physical arenas introduce real-world lighting shifts, unpredictable camera angles, and fast human movement. But the perception engine Ciris and his team had built under the extreme conditions of esports was already designed for exactly that kind of variability.

The expansion validated something Erhan Ciris had believed from the beginning: spatial intelligence is not specific to any one format. If your AI truly understands three-dimensional space in real time, the application scales across any live broadcast environment.

Where Erhan Ciris Sees 4D Sight Heading

Most people in this industry think the future of live media advertising is about sharper graphics or faster rendering. Ciris disagrees. The future, he believes, is spatial.

What 4D Sight has built is a Perception Layer, infrastructure that understands the physical world inside a live video feed. Virtual advertising is the first application, but it is not the last. Once a system can reason about depth, surfaces, and motion in real time, it opens the door to what Ciris thinks of as multimodal creative infrastructure. AI that works from spatial context, brand assets, historical footage, and live video simultaneously to modify and extend broadcast environments on the fly.

The idea that inspired all of this came from film. Ciris has long observed that the best product placements in cinema work because they live inside the world of the story. They do not interrupt. They do not compete for attention. They just belong.

Erhan Ciris is building 4D Sight toward a version of live media where monetization works the same way. Invisible to the viewer. Valuable to the rights holder. Native to the broadcast. That has been the vision since day one, and the spatial intelligence to make it real is already here.