Global bug bounty platform for AI models, where the global community tests and finds edge cases1-10 Employees
- B2B
- Early StageStartup in initial stages
- Top InvestorsThis company has received a significant amount of investment from top investors
- YC FundedStartup funded by Y Combinator
- Website
- Location
- Company size
- 1-10 people
- Total raised
- $5.8M
- Markets
Bobidi careers
We're building a platform that can scale bug bounty programs for AI models in the world.
Here’s how it works (With an example of a human detection model)
1) A customer (AI company) has an AI model that detects humans.
2) The customer connects their model with the Bobidi community using API.
3) Now the bug bounty event is created and the community tests the model: If a user takes a picture of a person and the model doesn’t recognize the object as a person, then she/he wins the reward. If a user takes a picture of a doll and the model thinks it’s a person, then she/he wins the reward, too.
4) After the validation, the customer (AI company) uses the dashboard to check how their model performed and purchases the pictures (i.e. edge cases) the users have found.
5) After retraining the model with the edge cases, the customer validates the AI model again with our community and compares how much it improved--the entire process becomes a loop.
Here’s how it works (With an example of a human detection model)
1) A customer (AI company) has an AI model that detects humans.
2) The customer connects their model with the Bobidi community using API.
3) Now the bug bounty event is created and the community tests the model: If a user takes a picture of a person and the model doesn’t recognize the object as a person, then she/he wins the reward. If a user takes a picture of a doll and the model thinks it’s a person, then she/he wins the reward, too.
4) After the validation, the customer (AI company) uses the dashboard to check how their model performed and purchases the pictures (i.e. edge cases) the users have found.
5) After retraining the model with the edge cases, the customer validates the AI model again with our community and compares how much it improved--the entire process becomes a loop.
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Jeong-Suh Choi
Total raised
$5.8M
Funded over
1 round
Latest round
Seed (Jul 2022)
MindTickle • Pune • 2 weeks ago
Matterport • United States • $142k – $222k • 2 weeks ago
Housecall • Remote • $96k – $120k • 2 weeks ago
Axiom Zen • Canada • 3 weeks ago
Quartzy • Houston • 3 weeks ago