REAL-WORLD DATA FOR PHYSICAL AI
The real-world data engine for Physical AI.
Bukla deploys trained workers and purpose-built capture systems to turn skilled work into high-quality, model-ready video data.
Site 031 — Bakery Line 2
Session context
- Task
- Tray loading
- Product
- Sourdough loaf
- Capture
- 6-cam wearable
- Session
- BKL-7A3F
Capture quality
Target: > 80%
Good lighting · Stable capture · Minimal occlusion
Capture system
6-camera wearable
Program status
- Cameras
- 6/6
- Capture
- Complete
- Processing
- Done
- Delivery
- Ready
- 0K+
- Hours / month
- 0%+
- Usable footage
- 0+
- Sectors
- 0
- Cameras per wearable
Useful data is engineered, not crowdsourced.
More footage does not mean better training data.
Physical AI models need more than large volumes of video. They need the right tasks, performed by the right people, in the right environments—and captured consistently enough to become useful training data.
Generic collection
- Random smartphone footage
- Uncontrolled environments
- Inconsistent camera angles
- Untrained contributors
- Low usable-video rates
- Limited connection to the model's target use case
The Bukla system
- Programs designed around the lab's use case
- Purpose-selected real worksites
- Trained workers and clear capture protocols
- Purpose-built six-camera wearables
- Proprietary processing and quality control
- More than 80% usable footage
How it works
From model requirement to real-world dataset.
- 01
Define the target use case
We work with your team to define the tasks, actions, environments, viewpoints, duration, and output requirements your model needs.
- 02
Source the right worksites
We identify real operational environments that match the use case—from food preparation to industrial production—and build the capture program around them.
- 03
Recruit and train workers
We select people who already know how to perform the work and train them on the capture protocol, equipment, and quality standards.
- 04
Capture real work
Workers perform authentic tasks using Bukla's purpose-built six-camera wearable system, creating rich footage of physical actions in context.
- 05
Process and deliver
Our proprietary technology processes and quality-controls the footage to maximize usable output and prepare it for the lab's data pipeline.
Every program is designed around what the model needs to learn—not around whatever footage happens to be available.
PURPOSE-BUILT CAPTURE
Six cameras. Real work. More useful data.
Bukla does not depend on workers holding a phone while trying to perform a task. Our wearable capture system is designed to record work naturally while providing consistent, multi-angle visual coverage of the action and its surrounding context.
Six-camera wearable
Body-mounted
Visual coverage
Built for natural work
The worker can focus on the task rather than filming it.
Richer visual coverage
Six cameras capture more of the action, tools, objects, and environment.
Consistent capture
Standardized equipment and training reduce variation between workers and sites.
Quality engine
Quality is designed into the entire operation.
Bukla optimizes every stage of the capture pipeline to increase the amount of footage that can actually be used for training. Today, more than 80% of the video we capture is usable.
Integrated quality system
- 01Use-case design
- 02Worksite selection
- 03Worker selection
- 04Worker training
- 05Standardized capture
- 06Proprietary processing
- 07Quality control
Raw capture
Usable training data
0%+
Usable footage
BUILT TO SCALE
The environments your models need. At the volume they require.
Bukla combines worksite access, trained workers, capture operations, and proprietary technology to produce more than 100,000 hours of real-world footage every month across more than 40 sectors.
Restaurants
Bakeries
Factories
40+
Work environments
Bukla sources environments based on each lab's target use cases.
- 100K+
- Monthly recording capacity
- 40+
- Sectors and work environments
- 80%+
- Usable footage
- One
- Operating system from sourcing to delivery
Why Bukla
A data partner built specifically for the physical world.
Use-case-first
Every capture program starts with what the model needs to learn.
Real operational environments
Capture authentic work where it actually happens—not staged approximations.
Trained skilled workers
The people performing each task understand both the work and the capture protocol.
Quality at scale
Proprietary technology and rigorous operations produce high volumes without accepting low usable-data rates.
What does your model need to learn next?
Tell us the tasks, environments, and scale you need. Bukla will design the capture operation around them.