One piece or the whole pipeline. Built by a team that shipped photorealism for film, Deadpool and Furious 7 among the credits, then Microsoft HoloLens and Meta Reality Labs.
Physics-accurate replicas of your facility, field, or machine. From photos, scans, CAD, or BIM. The stage every other station runs on.
Weather, lighting, wear, rare events, sensor physics. The situations your robot must survive, staged safely and repeated endlessly.
RGB, depth, segmentation, poses, LiDAR from the same scene, pixel-exact. The coverage no collection effort reaches.
Detection, segmentation, pose, tracking. Trained on synthetic and real footage, benchmarked against reality before you trust it.
Policies trained in simulation: grasping, navigation, manipulation. Reinforcement learning and imitation, stress-tested across thousands of virtual runs before the robot moves once.
Cloud pipelines, GPU inference, edge delivery. Models that leave the lab and hold up on the floor. Infrastructure your future hires inherit.
Bring the problem. We run the pipeline end to end while you build your team, and hand over everything when you're ready.
stylized previews · curious how the pipeline works? watch a short demo ▸ · + grasp points · COCO · KITTI · YOLO · your schema
Clinical AI trained on zero patient images. Validating in 2 hospital systems.
Discover ›Pipeline engineer and technical director since 2014, across Hollywood film and animation studios. Twelve credits on IMDb, House of Cards to Swapped.
Full credits on IMDb ›Member of the VES, the entertainment industry's honors society for the artists and engineers behind film's visual effects.
VES member page ›Film set the realism bar. Shipping real-time rendering and spatial computing on devices people wear set the engineering bar. Binary Core points both at robots.
You bring your hardest physical AI problem. We listen, ask the right questions, and within a day you get one page on exactly how we would attack it, yours to keep either way.
Book twenty minutesWant proof before a conversation? Send one photo of your environment. We rebuild a slice of it and return labeled frames from stations 01 through 03, the front half of the line, judged on your own screen.
Whatever the fix needs: digital twins, simulation, training data, models, deployment, or the whole line running as one. Starts as a scoped pilot, benchmarked on your real footage. You keep everything, pipeline included.
More. Data is one station on the line. Teams bring us whatever blocks perception: no digital twin, no simulation, models stuck in the lab, no deployment path. We build the missing piece, or run the whole pipeline while you hire. And past seeing: we train the acting too, policies in simulation, ready for the real robot.
Both. Perception models teach the robot to see. In simulation we also train how it acts: grasping, navigation, manipulation policies through reinforcement learning and imitation, refined across thousands of virtual runs, then benchmarked on the real system.
Yes, when the sim is built right. Domain randomization forces the model to learn the object, not the render. Every pilot is benchmarked on your real footage first.
No. Asset creation happens inside our pipeline: procedural, photogrammetry, or AI assisted. You never source a model.
Intrinsics, mounting, and noise are matched. Depth, stereo, and LiDAR come from the same scene, perfectly registered.
Keep it. The best results blend both. Synthetic covers what real cannot: new SKUs, rare defects, scenes you will never stage.
You do. Images, labels, models, and the USD sim transfer in full. Pipeline included if you ever take it in-house.
Twenty minutes. You talk, we listen, and you leave with a one-page attack plan, yours either way. Then you decide. Whichever station your problem lives in, this is the door.
Book twenty minutes