Solutions / Physical AI & Robotics
Real-world data for Physical AI & Robotics
Human demonstrations and multimodal capture for embodied systems.
We design and run capture protocols for manipulation and real-world tasks — egocentric, synchronized multi-camera, RGB-D and sensor data, delivered calibrated and documented.
What we produce
Every dataset is designed around your model's requirements and delivered with metadata, QA and rights in place.
Data
- 01
Human demonstrations
Real people performing the task, repeated across operators, objects and conditions.
- 02
Human-object interaction & manipulation
Grasping, placing, assembling and handling objects, with hands and objects in view.
- 03
Tool use
Real tools used for real tasks, with the hand, tool and workpiece captured together.
- 04
Egocentric / POV
First-person view from the demonstrator's head or chest, hands and objects in frame.
- 05
Synchronized multi-camera
Fixed and wearable views of the same action on one timeline.
- 06
RGB-D & spatial capture
Color, depth and 3D scene geometry for reach, placement and navigation.
- 07
Hand & body motion
Hand, arm and body movement captured alongside the video.
- 08
Failure & recovery
Failed attempts, retries and recoveries recorded on purpose where needed.
How we run it
- 09
Protocol design
Task scripts, scenarios and variation plans written around your policy.
- 10
Capture systems
POV rigs, camera arrays, RGB-D, IMU and force/contact sensors as required.
- 11
Synchronization & calibration
Streams time-aligned and every setup calibrated and logged.
- 12
Metadata & QA
Task, environment and sensor details stored and checked for every session.
Our process
- 01
Requirements
Define the model task, target behaviors, constraints and success criteria.
- 02
Specification
Translate project requirements into scenarios, capture parameters, metadata structure, deliverables and QA criteria.
- 03
Pilot
Produce a small sample batch, review it with your team, and lock the spec before scaling up.
- 04
Production
Produce, collect or source the data with the required metadata, rights and releases in place.
- 05
QA
Review samples, fix inconsistencies, and validate metadata, structure and annotations where required.
- 06
Delivery
Hand over a clean, documented, rights-ready dataset in your preferred format.
- 07
Scale
Grow volume, locations and variations on the same pipeline as your model needs more data.
Why Kvet
Built around your requirements
Every project is built around the specific data, environments, actions and capture conditions required.
Production-first
We organize the participants, environments, interactions and capture setups required to produce data that does not already exist.
Multiple production models
Controlled production, distributed collection and content sourcing can be used independently or combined within one project.
Visual and technical depth
Image and video production, egocentric and multi-camera capture, RGB-D, creative workflows, 3D, VFX and multimodal data within one production ecosystem.
From pilot to scale
Validate the approach with a focused pilot, then scale across participants, locations and countries.
Structured delivery
Rights, releases, metadata, QA and technical requirements are integrated into the production pipeline.
