Humanoid robotics teams
For teams training new skills, improving hand manipulation, imitation learning pipelines, and teleoperation workflows.
Humanoid & Physical AI · Data programs
Real-world data programs for humanoid and physical AI teams
HumanoidLayer helps robotics companies launch custom collection programs for hand, manipulation, and task data through trained contributors, partner workforces, quality control, and buyer-specific delivery workflows.
- Video-based and glove-based capture
- Buyer-specific specs
- QC before delivery
- Pilot batch programs
Buyer-specific specQC-backed deliveryPilot-first
- Program
- Hand manipulation pilot
- Setup
- Glove capture
- Status
- QC in progress
- Accepted episodes
- 184
- Delivery
- Batch ready
1
Buyer Spec
Spec defined
2
Capture Program
Collection active
3
QC
QC in progress
4
Delivery
Batch delivered
Not raw uploads. Managed data programs built around your spec.
HumanoidLayer helps robotics companies run structured real-world data collection programs for specific tasks, environments, and modalities.
Instead of collecting random uploads, we turn your requirements into a working production pipeline:
- task definitions
- capture protocol
- metadata schema
- contributor instructions
- quality control rubric
- accepted batch delivery
Supporting modalities
- Hand and manipulation data
- Repetitive task workflows
- Egocentric task video
- Buyer-specific metadata and QC
- Pilot-first batch delivery
Built for robotics teams that need real-world data
Physical AI and embodied AI labs
For teams that need real-world task episodes beyond simulation and synthetic datasets.
Manipulation and teleoperation teams
For teams that need grasp sequences, hand motion, object interaction data, and repetitive task demonstrations.
Warehouse and service robotics companies
For teams working on real operational scenarios who want to launch targeted dataset pilots quickly.
How HumanoidLayer works
- 01
You define the spec
Tell us what data you need: tasks, modalities, setup, quality thresholds, metadata, volume, and delivery requirements.
- 02
We turn it into a collection protocol
We design the workflow, contributor instructions, schema, QC rubric, and batch structure.
- 03
Contributors or partner teams capture the data
We run the program through trained contributors, existing physical workforces, or pilot teams in selected verticals.
- 04
We review and deliver accepted batches
We run QC against the agreed criteria and deliver accepted data in a structured format.
Two capture modes for different tasks and budgets
Choose the setup that matches your modality, signal requirements, and pilot timeline.
Video capture
Setup 1 — Video Task Capture
A faster, more scalable option for collecting task data through video and structured metadata.
Includes
- chest-mounted or head-mounted camera
- optional hand-side view
- task logging through app or phone
- episode segmentation
- structured metadata per task
Best for
- egocentric task video
- workflow capture
- repetitive physical tasks
- success / fail labels
- before / after context
Useful in
cleaningpackingsortinginspectionsservice workflowshousehold or warehouse tasks
Advantages
- faster to deploy
- lower equipment cost
- easier worker onboarding
- ideal for pilot programs
Glove capture
Setup 2 — Glove Hand Capture
A higher-value setup for precise hand, finger, and manipulation data.
Includes
- data gloves
- hand and finger motion capture
- task and object tagging
- optional validation camera
- structured export for robotics workflows
Best for
- finger pose
- hand pose
- grasp sequences
- repetitive manipulation episodes
- object-specific interaction tasks
- teleop-compatible datasets
Useful in
packagingassemblyrepetitive hand workflowsrepair-like tasksmanipulation learningdexterous task pilots
Advantages
- more valuable data
- better fit for hand-centric robotics models
- stronger signal for imitation learning
- premium batch potential
What HumanoidLayer can collect
- Hand manipulation episodes
- Finger and grasp sequences
- Repetitive workflow tasks
- Egocentric task video
- Object-specific interaction data
- Failure and recovery cases
- Human task demonstrations
- Structured task metadata
- Quality-screened accepted batches
Need a custom format or schema? HumanoidLayer can support buyer-specific protocols and delivery requirements.
Quality
Quality-first by design
Different robotics teams need different standards for data quality, annotation, metadata, and delivery format. HumanoidLayer is built as a managed production system, not a generic upload stream.
- buyer-specific acceptance criteria
- protocol-based capture
- metadata schemas
- QC before delivery
- accepted / rejected pipeline
- privacy-aware workflows
- standardized core + client-specific fields
- structured batch delivery
You define the standard. We run collection and acceptance against that standard.
Why use HumanoidLayer instead of building every workflow internally
Building internally
- design collection ops from scratch
- recruit and manage contributors
- build capture SOPs
- set up QC workflows
- create batch delivery pipeline
- slow time to first pilot
With HumanoidLayer
- launch with a pilot
- start from a working program structure
- use two proven capture modes
- access managed contributor workflows
- receive QC-backed accepted batches
- reduce time to initial data delivery
HumanoidLayer acts as an external execution layer for robotics data collection, not a replacement for your ML or research team.
Where HumanoidLayer is most useful right now
- 01when you need real-world demonstrations beyond simulation
- 02when you want to test a new hand or manipulation dataset quickly
- 03when your team has data needs but no ready external collection pipeline
- 04when you want an external execution layer without building ops internally
- 05when you need quality-screened batches under your own spec
- 06when you want to validate a new collection workflow before scaling it
How we start working together
- 1
Intro call
You share the use case, data type, and target deliverable.
- 2
Spec definition
We define tasks, modalities, QC criteria, volume, timeline, and delivery format.
- 3
Pilot program
We launch a small paid pilot batch.
- 4
Review and iterate
We review samples, refine protocol, and align on acceptance criteria.
- 5
Scaled collection
We move into recurring batch delivery or an ongoing data program.
FAQ
No. HumanoidLayer uses a standardized core but supports buyer-specific metadata, QC rules, and delivery structures.
Yes. Pilot-first engagement is the preferred way to align on format, quality expectations, and workflow.
No. HumanoidLayer supports both video-based capture and glove-based hand capture.
Yes. HumanoidLayer runs managed collection programs through contributors and partner workforces.
Each program runs against a defined QC rubric. Data is reviewed against agreed requirements before delivery.
Yes. We can run task-specific programs around defined actions, objects, workflows, or environment types.
Launch your first pilot data program
Tell us what your robotics team needs, and HumanoidLayer will propose the right collection setup, QC flow, and pilot structure.
Pilot-firstBuyer-specificQC-backed