Alternatives to 6thSense

Open-source Python SDK and CLI for training and deploying physical AI models — VLA and SLM — from managed cloud compute to real robot hardware.

Applied research lab that captures expert reasoning and structures it into SFT, RL rubric, agent, and computer-use training data for frontier models.

Cortex AI supplies real-workplace egocentric video and robot trajectory data for training embodied AI models.

Early-stage San Francisco robotics lab building policies for robots that do real work, and hiring its first researchers.

Traverse is a research lab producing expert-captured training data that gives frontier models taste and judgment for ambiguous, long-horizon work.

Industrial robot manipulation platform that learns dexterous tasks from a single sentence and proves each skill with an auditable success rate.

Modular humanoid robot platform for builders collecting data, training skills, and deploying autonomous robots.

Skild AI is building an omni-bodied robotic brain to control any robot for any physical task.

Rhoda AI builds video-predictive robot foundation models that learn heavy industrial manipulation tasks from a single human demo.

Physical Intelligence (π) builds vision-language-action robot foundation models — one generalist policy for any manipulation task.

License Nuro's proven L4 self-driving system for robotaxis, commercial fleets, and personal vehicles.

Build-it-yourself open-source quadruped robot kits — Bittle dog, Nybble cat, and the new Quaddle — that you assemble and then program in block code, Python, or

Open-source simulated benchmark for language-conditioned, long-horizon robot manipulation from the University of Freiburg.

Custom audio datasets for training and evaluating voice AI, scoped to your model's spec.

GameEngineBench benchmarks and UE5 training data for AI agents that write real game-engine code.

Applied AI research company building foundation models that let robots, drones, and industrial machines act in the physical world.

Snorkel AI builds expert training data, evals, and runnable environments for frontier models and agents.

Open source dev kit for AI-native robotics with leader-follower teleoperation.

Audio datasets built like research artifacts for teams training speech recognition, translation, synthesis and voice-interaction models

Multimodal real-world human data for training embodied AI agents

Zeon Systems converts natural-language experiment prompts into simulated, robot-executed wet lab protocols.

Mapless, vehicle-agnostic driving intelligence that scales autonomous driving from L2 to L4 by learning from data instead of relying on HD maps.

Open-source, multimodal data annotation platform for image, video, 3D point cloud, and audio labeling—self-hosted, cloud, or fully managed

Open-source autonomous driving simulator built on code and protocols you can inspect, with Unreal Engine 5.5 and ROS2 integration.

Offline AI image annotation for YOLO and VOC datasets — local SAM2, SAM3 and YOLO-World, one-time purchase from $49.

Open-source Python toolkit that auto-labels images with big foundation models, then trains small fast vision models you own.

Structured3D: a 3,500-design photo-realistic synthetic dataset with dense 3D structure annotations for scene-understanding research.

Open-core LiDAR SLAM for ROS 2: odometry, LIO, 3D SLAM and geo-referencing you can modify at the source level.

Human-recorded computer-use datasets that teach AI agents to operate real software the way people do.

The first large-scale open V2V cooperative perception benchmark — 73 scenes, 12K frames, 16 models, from UCLA Mobility Lab.