NeuroTensor Labs builds proprietary Vision-Language-Action (VLA) foundation models that deliver sub-8ms spatial geometry and obstacle reasoning for autonomous mobile robots, aerial drones, and industrial manufacturing lines.
Experience how NeuroTensor's compiled spatial foundation model processes high-frequency sensor streams, zero-shot bounding boxes, and metric depth in sub-6ms cycles.
From multi-camera spatial reasoning to ultra-compact robotic execution, our unified architecture powers autonomous agents across cloud, on-prem clusters, and embedded edge compute.
Our multimodal Vision-Language-Action foundation model pre-trained on 400B spatial tokens. Unifies dense 3D geometry prediction, spatial semantic affordances, and zero-shot trajectory generation into a single end-to-end transformer.
Proprietary compiler toolchain that compiles large spatial neural networks into hyper-optimized Tensor TensorRT execution engines, generating sub-8ms deterministic runtimes for Jetson AGX Orin & Thor.
Synthetic data simulation pipeline built upon Tensor Isaac Sim and Omniverse USD assets. Synthesizes millions of edge-case physical failure scenarios, lighting shifts, and extreme physical dynamics to pre-train robust edge agents.
Pre-training large spatial VLA models requires massive distributed GPU clusters. NeuroTensor Labs leverages high-performance accelerator allocations to train our next-generation 70B spatial foundation model across multi-node 80GB SXM5 clusters.
Dynamic estimation based on Chinchilla compute scaling laws
Comprehensive presentation covering the market problem, TAM ($48.5B), proprietary CUDA/TensorRT architecture, traction benchmarks, and compute expansion milestones.
NeuroTensor Labs is founded and directed by Tanaji Vishnu Yadav, combining frontier AI research from Stanford AI Lab with industrial GPU systems engineering.
Lead AI Systems Architect • ex-Stanford AI Lab
Tanaji Vishnu Yadav holds a Ph.D. in Computer Science from the Stanford Artificial Intelligence Laboratory (SAIL), specializing in self-supervised 3D scene representation networks, spatial foundation models, and real-time vision-action policies for embodied physical systems.
As Founder and CEO, Mr. Yadav directly directs the company’s end-to-end technological execution: from proprietary NeuroVoxel-1 spatial foundation model pre-training regimens to hardware-aware compilation on Edge AGX Orin, next-generation Thor, and 80GB SXM5 GPU clusters.
"We are entering an era where robots will perceive geometry not as isolated bounding boxes, but as rich, actionable spatial affordances. Running that intelligence at 120 FPS on an embedded 275 TOPS edge chip changes everything."
Our foundation architecture is built upon rigorous mathematical proofs and published spatial geometry benchmarks.
Tanaji Vishnu Yadav (Lead AI Architect & Founder, NeuroTensor Labs)
Tanaji Vishnu Yadav, NeuroTensor Research Group
Join our closed developer pilot for robotics OEMs, autonomous vehicle labs, and industrial automation teams. Pre-compiled TensorRT engines delivered directly to your engineering team.
