The Problem
The market is producing millions of hours of first-person human activity video, but raw egocentric footage is not the same thing as training-ready data.
Raw hours are not coverage
Frontier models and robotics teams need the right tasks, environments, objects, movements, failure modes, and real-world variation — not endless repetition of the same footage.
Footage is not training data
Useful physical AI data needs labels, sensor alignment, provenance, rights, chain of title, and delivery formats that model teams can actually use.
Model fit is the value
Flikforge's data foundry turns rights-cleared human activity video into curated, coverage-scored, model-ready training data built around what the system needs to learn.
The Flikforge Solution
Frontier labs and robotics teams do not need the same dataset. The Flikforge EmbodiedAI family separates breadth and depth into two purpose-built tiers.
Flikforge EmbodiedAI-500k
More than 500,000 hours of rights-cleared human activity video, curated to provide broad coverage across environments, geographies, task families, objects, human behaviors, and real-world variation.
Designed for
Robot foundation models, world models, multimodal systems, frontier AI labs, and large-scale physical AI pretraining.
Flikforge EmbodiedAI-75k
75,000 hours of skill-aligned training data built around 1,000+ robotic primitive skills, domain-specific coverage, critical variation axes, failure modes, recovery behavior, and training-ready delivery.
Designed for
Robotics teams, humanoid developers, dexterous manipulation programs, industrial automation, household robotics, service robotics, and embodied AI systems.
Every segment in both tiers is sourced with consent, commercially licensed, and delivered with Flikforge's patent-pending AI Rights Certificates — provenance and chain-of-title embedded in the data layer itself.
Engineered Skill Coverage
EmbodiedAI-75k is organized around the specific skills robots need to perform real-world tasks reliably — with coverage defined before capture, not discovered after the fact.
Skill-defined coverage
Each dataset is mapped to robotic primitive skills such as opening, picking, placing, sorting, stocking, pouring, retrieving, inspecting, cleaning, and manipulating objects in real-world environments.
Variation by design
Skills are captured and selected across the variation axes that matter for generalization: objects, surfaces, lighting, clutter, grips, handedness, camera perspective, failure modes, and recovery behavior.
Training-ready delivery
Segments are prepared with dense labels, sensor-aware structuring, provenance, rights, and delivery formats designed for robot training workflows — not raw footage handoff.
Domain coverage
Household robotics · Commercial environments · Healthcare environments · Industrial automation · Public service robotics · Entertainment and companionship systems
Ready to scope Flikforge EmbodiedAI?
Explore the Flikforge EmbodiedAI family—compare EmbodiedAI-500k breadth with EmbodiedAI-75K engineered depth, or request a custom data schema built around your model, robot, or deployment environment.