AI annotation & evaluation
Embodied AI and robot-video annotation
Annotate robot-operation video against timestamps or frame ranges. Tasks cover multiple views, action segments, left/right/both grippers, object states, English action descriptions and task/action reasoning grounded in visible evidence. The workflow has been validated on public robot footage and supports pilots on project material.
Request a sample ↗What to confirm before requesting a quote
- Coverage
- Regions, languages, date range and available record count
- Fields and attachments
- Field definitions, example records and whether original documents or media are required
- Quality and updates
- Deduplication and missing-value rules, sample-based acceptance criteria and update frequency
- Permitted uses
- Internal research, model training, customer-facing products or redistribution
These are project scoping questions, not a statement that every data type includes all coverage or permissions.
01 / WHAT’S INCLUDED
What’s in the dataset
- Source-video IDs, camera views and time/frame mappings
- Action ranges, classes, gripper sides and state changes
- English descriptions, subtasks, observations and reasoning/CoT
- Error attributes, individual results and provenance
02 / USE CASES
Where it can help
- Embodied AI and VLA data preparation
- Robot-task understanding and video retrieval
- Operation-step, failure and correction analysis
03 / DELIVERY
Choose the data you need
Receive JSON linking segments, frame ranges, text and sources, preserving individual annotators and prediction versions.
Start from blank annotations or review a prediction. Agree examples, reviewer roles and output format before scaling.
See a sample format ↗Assess the fit for your project
Start with real footage to align camera views, frame ranges, descriptions and task reasoning.
Do you support multiple views and English action descriptions?
The workflow supports multiple views, per-segment English text and action attributes. Confirm synchronization, segmentation and approved examples on project footage.
How is reasoning/CoT annotated?
Use the agreed template for tasks, subtasks, observations and action rationale, retaining uncertainty. Descriptions do not claim access to a robot's internal thoughts.
Sources and usage
Use a real-material pilot to confirm view synchronization, segmentation, fields and throughput. Box/point editing, 3D relations and control-format conversion require task-specific adaptation.
If you plan to train a model, use the data in a customer-facing product or share it with third parties, mention this when requesting a quote so we can check source permissions and restrictions.
Public access does not establish permission for collection, training or redistribution. Naming a platform does not imply affiliation, agency or endorsement.
Read about data sources and rights ↗Want to review a sample first?
Tell us your project objectives and we’ll help you assess and find a relevant sample.