Turn human expertise and the physical world into data AI can learn from.
The data layer of the FelixSphere stack. Expert-generated training and evaluation data, delivered with a record of how every example was made, and expanding into robotics and world-model data.
Source. Generate. Review. Evaluate. Exchange.
Find the people and the real-world captures a model needs.
Experts answer, solve, demonstrate, and critique.
Independent reviewers decide what passes.
Measure quality and coverage against held-out sets.
Deliver or list datasets with verifiable provenance.
Data for models, for robots, and for world models.
Data for training, tuning, and evaluating models.
- · Pre-training
- · Post-training
- · Expert-generated
- · RL and preference
- · Evaluation and benchmarks
- · Enterprise datasets
Data for robots that act in the physical world.
- · Ego-view
- · Wrist camera
- · UMI
- · Tactile
- · Teleoperation
- · Human demonstrations
Data for models that understand how the world works.
- · Video
- · Multimodal
- · Spatial
- · Physical-world observation
- · Real-world interaction
- · Video-language
You don't have to take our word for any of it.
Experts are qualified, not assumed
Credentials are checked and every domain is earned through a calibration task. Qualifications can be revoked.
The work is recorded
Each record carries evidence of how the answer was reached.
Someone else decides
Independent reviewers score the work before it ships. Provenance is sealed so buyers can verify it.
Give AI something worth learning from.
Bring your own experts, buy from the market, or have FelixSphere source and produce the dataset.