Video Collection → AI Training Data Pipeline
Automate the collection, organization, and processing of user-submitted videos for AI model training using cloud storage and computer vision APIs.
Workflow Steps
Typeform
Create video submission form
Set up a form with video upload capabilities, participant consent, task instructions, and metadata fields like task type, language, and participant demographics.
Zapier
Trigger on form submission
Connect Typeform to trigger automation when new video submissions arrive, capturing all form data and video file URLs.
AWS S3
Store videos in organized buckets
Automatically upload videos to S3 buckets organized by task type, date, and participant ID. Set up proper IAM permissions and lifecycle policies.
AWS Rekognition
Extract video metadata
Use Rekognition Video API to detect objects, activities, text, and faces in submitted videos. Generate confidence scores and timestamps for each detection.
Airtable
Track training data inventory
Create a database to track video assets, AI analysis results, training status, and quality scores. Include fields for manual review flags and approval status.
Workflow Flow
Step 1
Typeform
Create video submission form
Step 2
Zapier
Trigger on form submission
Step 3
AWS S3
Store videos in organized buckets
Step 4
AWS Rekognition
Extract video metadata
Step 5
Airtable
Track training data inventory
Why This Works
Combines form collection with cloud storage and AI analysis to create a scalable pipeline for processing thousands of training videos with minimal manual intervention.
Best For
AI companies collecting video training data from distributed contributors
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