Overview
How the platform works
KGeN Quest connects everyday people with labs that train physical AI. You record real daily tasks, the platform validates and prepares the data, and you are paid for approved hours.
Complete cycle
From registration to payment
Six stages that repeat each recorded session.
1. Registration and verification
You create the account, confirm the email and pass the unique human verification. Each participant has an identity verified on the network, which guarantees data origin.
2. Choice of activity
The dashboard shows the open campaigns in your country, with value per hour, target of hours and whether the activity is normal or special.
3. Recording and Sending
Record a first-person session with your phone secured in a head mount, then upload it through the app. The session enters the review queue.
4. Quality Review
The team checks stability, lighting, duration, task compliance and privacy. Approved sessions count as valid hours; sessions that do not meet the standards receive a strike.
5. Preparation of the data
Preparing video data for AI may involve selection, annotation and organization by activity. Check the platform terms for each campaign’s uses and recipients. Ordinary video does not directly measure force or touch.
6. Payment
Approved hours are converted into a US dollar balance, together with applicable daily and weekly bonuses and referral commissions.
Why It Exists
Robots learn from real people
Real task videos can support the study of actions and interactions with objects. Robot training also depends on models, other data and tests: observing an activity is not equivalent to performing it.
Human signal
Sequences of actions and interactions with objects recorded during a real task.
Local context
Brazilian kitchens, workshops and businesses with their own objects and routines.
Scale verified
The origin, permissions and quality criteria need to be documented by the project.
From your first question to your first recording
Understand the extra income with videos for AI, check out the participation and learn the concepts behind data collection.
Participation and extra income
Earning money by training AI: how video collection works
Learn about extra income from videos for AI, how it differs from creating AI-generated content, and how to assess tasks, costs and approved hours.
Earn money recording videos at home: getting started
Learn how recording everyday activities for AI works: devices, available tasks, privacy, uploads and approval. Extra income without relying on followers.
Record household tasks for AI: examples and preparation
Understand how to film household tasks for data collection: dishes, clothes and organization, with framing care, security and approval.
Does KGeN really pay? Assessing trust and payments
See what is announced about KGeN payments, what to check in the statement and what evidence to evaluate before recording tasks or buying equipment.
Minute Data: how the AI recording app works
Understand Minute Data, registration, organization code, compatible mobile phone, and video submission. See how to separate app, campaign, and payment.
Minute Data: upload errors, camera issues and missing hours
Learn what to check when Minute does not send videos, shows unsupported camera, or when hours do not appear in the campaign after upload.
Physical AI, robotics and privacy
How videos help in training humanoid robots
Understand the collection of videos for robotics, the role of human demonstrations and the limits between observing a task and performing it with a robot.
What is physical AI and how it relates to robotics
Learn about physical artificial intelligence, the difference for chatbots and the role of videos, sensors, simulation and tests in the real world.
First-person videos: what is egocentric data?
Understand POV and egocentric videos, how to show hands and objects and what to check before recording a task for data collection.
Privacy when recording videos for data collection
Practical checklist to prepare the environment, avoid personal data in the frame and check permissions before sending task videos.