Commercially licensable first-person video, global sourcing capacity, and purpose-built in-the-wild collection for models that need to understand how people see, move, manipulate objects, and interact with real environments.
Pangeanic's current identified inventory exceeds 6,500 hours and continues to grow every week. Established supply agreements and sourcing chains across multiple continents provide access to more than 20,000 hours worldwide, while custom programs can be designed around specific tasks, devices, environments, participants, geographies, and model requirements.
Pangeanic combines directly identified egocentric video inventory, established international supply agreements, and custom collection. The right route depends on the required tasks, environments, viewpoints, devices, participants, geographies, technical specifications, and permitted uses.
Pangeanic has more than 6,500 hours of currently identified commercially licensable egocentric video, including substantial collections across Latin America and Asian manufacturing environments.
Representative samples · Inventory summary · Task coverage · Recording specifications · Available metadata · Narration details · Delivery schedule · Commercial AI and ML licensing terms
Established supply agreements and data sourcing chains across multiple continents give Pangeanic access to a substantially larger pool of egocentric video. Candidate collections are qualified against the actual project requirements before commercial commitment.
Geography · Environment · Task type · Camera configuration · Recording duration · Narration · Metadata · Permitted use · Licensing conditions · Delivery readiness
When existing footage does not match the required deployment conditions, Pangeanic can design a new in-the-wild collection around the model, task, environment, participant population, geography, device configuration, and quality thresholds.
Pilot collection · Scenario design · Contributor recruitment · Wearable and multi camera capture · Device specifications · Synchronization · Narration · Metadata · Quality control · Recollection rules · Annotation · Secure delivery
Procurement note: We validate exact availability, jurisdictions, permitted uses, task coverage, technical specifications, synchronization requirements, and licensing conditions against current inventory and supply agreements before commercial commitment.
Pangeanic structures egocentric video programs around explicit capture protocols and acceptance rules. Before collection scales, the protocol defines what participants must do, which viewpoints and devices are required, how multiple cameras are synchronized, what must remain visible, which metadata travels with every recording, and what causes footage to be rejected or recollected.
Tasks and subtasks are defined before collection begins, including start and end conditions, objects, tools, expected outcomes, permitted variations, interruptions, and failure cases.
Programs can specify head mounted, chest mounted, wrist, handheld, mobile, robot mounted, or multi camera configurations together with camera position, orientation, resolution, frame rate, field of view, recording duration, and environmental conditions.
Where the model requires coordinated perspectives, collection can include synchronized cameras and associated audio or sensor streams. The protocol defines timing tolerance, recording start and stop behavior, file relationships, and synchronization validation.
Narration can be captured while a task unfolds or added afterward. The choice depends on whether the model needs concurrent reasoning, natural verbalization, cleaner retrospective explanation, or a combination of these signals.
Structured metadata can describe task, geography, environment, language, device, camera configuration, participant attributes, duration, objects, validation status, and permitted use. Optional annotation can add temporal segments, action labels, object references, transcription, captions, and event boundaries.
A pilot calibrates automated checks and human review against explicit thresholds for visibility, framing, task completion, synchronization, audio, metadata, technical integrity, and protocol compliance. Rejection, recollection, escalation, and delivery rules are agreed before production volume increases.
Pilot first: custom egocentric programs normally begin with a controlled pilot that tests capture instructions, devices, synchronization, contributor behavior, data quality, metadata, and rejection criteria before the collection is expanded.
Physical AI systems need more than object recognition. They must understand actions over time, relate language to visible behavior, predict how environments change, and learn which action should follow from the current state. Egocentric video brings training data closer to the viewpoint from which those systems will eventually operate.
First person demonstrations can capture reaching, grasping, sorting, assembly, tool use, inspection, opening, closing, carrying, household tasks, and industrial operations from a viewpoint relevant to systems learning physical interaction.
Egocentric video can be paired with instructions, narration, transcriptions, action labels, and task outcomes to train systems that must connect what they see and hear with what should happen next.
Longer sequences preserve the relationship between state, action, consequence, correction, and outcome. These temporal structures can support models learning how the physical world evolves rather than treating video as a succession of unrelated frames.
Narration, transcription, captions, object references, instructions, and structured metadata can connect visual events with human intent, terminology, decisions, and explanations.
Extended recordings can retain preparation, intermediate decisions, dependencies, mistakes, recovery actions, interruptions, and task completion, creating richer supervision for systems that must reason across longer action sequences.
First person datasets can support activity recognition, AR and wearable systems, maintenance assistance, inspection, logistics, procedural guidance, safety workflows, and models operating alongside people in real environments.
First-person footage can reveal participants, bystanders, workplaces, homes, screens, documents, voices, location cues, and operational environments. Commercial usability therefore depends as much on provenance, permissions, privacy controls, licensing, and traceable delivery as on image quality.
Pangeanic connects these requirements through governed AI Data Operations so procurement, technical, legal, and model teams can evaluate the same data asset against a common set of evidence.
Review collection origin, contributor permissions, relevant usage rights, and supporting documentation under the agreed procurement and licensing framework.
Review, filtering, exclusion, and masking workflows can be applied where faces, screens, documents, identifiers, voices, or sensitive surroundings require additional control.
The selected data's permitted uses, restrictions, training rights, derivatives, exclusivity, term, redistribution conditions, and other commercial requirements are defined.
Prepare video files, metadata, validation results, manifests, documentation, and associated annotations according to the agreed delivery schema and secure transfer process.
