01
Accept a task
Choose an available car interior cleaning data collection task.
Demonstration data for physical AI
Data infrastructure for robotic car interior cleaning.
Autosnabb collects high-quality, first-person cleaning demonstrations for the next generation of embodied AI and Vision-Language-Action systems.
First-person
Cleaning demonstrations recorded from the worker's perspective.
Structured
Standardized tasks, instructions, metadata and quality checks.
Scalable
A distributed contributor network designed for diverse environments.
Contributor workflow
How it works
Contributors complete clearly defined cleaning tasks and submit standardized demonstration data.
02
Record the session
Follow the recording instructions and capture the cleaning process.
03
Upload the data
Submit the video and required information through the platform.
04
Get paid
Approved data submissions are compensated according to the task.
Contributor network
Turn real cleaning work into valuable training data.
We are building a network of people who understand real vehicle interiors and can capture careful, repeatable demonstrations.
Suitable for
- Professional detailers
- Mobile car care operators
- Car wash businesses
- Automotive enthusiasts
The full contributor platform is under development.
For companies
Tell us what training data you need.
Autosnabb is in its early stages. We are actively listening to robotics and embodied AI teams and building the platform around real-world data requirements.
If you are developing robotic cleaning systems, Vision-Language- Action models or other physical AI applications, we would like to understand your challenges and explore what data would be useful.
Start a conversationWe want to learn about
- Custom first-person demonstrations
- Vehicle-specific task data
- Diverse interiors and environments
- Structured collection campaigns
Building with early partners
Early partners can help shape task definitions, metadata, recording standards and the overall data collection workflow.
Why Autosnabb
Robots perform well in structured factories. Everyday physical work remains much harder.
Vehicle interiors contain varied materials, shapes, objects and levels of contamination. Autosnabb is building the demonstration data needed to help robotic systems understand and perform these complex tasks.