AI Visual Data Collection Sprint for a Generative Vision Model
Challenges:
The client needed diverse visual datasets to train a generative vision model, but existing sources lacked demographic balance. Underrepresentation of non-Western groups led to biased outputs and reduced realism. This data gap hindered fairness, accuracy, and global model scalability.
Industry:
Artificial Intelligence / Computer Vision / Data Annotation
Solutions:
SummitNext implemented a globally coordinated data collection sprint, leveraging verified contributors, localized recruitment, and dual-layer quality control to meet demographic and technical standards.
Results:
Achieved 96% compliance with client requirements, collected 30,000+ high-quality visuals from 5,000 contributors, and ensured balanced demographic representation across five major countries — enabling the client’s AI model to perform more accurately and ethically.
About the Client
The client is a leading global AI company specializing in generative vision models. With growing concerns about dataset bias and inclusivity, the company sought to enhance its training data diversity by capturing balanced facial images from underrepresented demographics across multiple regions.
However, gaps in representation from countries like India, the US, Canada, China, and Pakistan limited the model’s fairness and generalization ability.
Case Overview
SummitNext Technologies, a Malaysia-based BPO and data services company, collaborated with the client to execute a six-month large-scale image collection project. The initiative focused on curating demographically diverse visuals while maintaining strict technical and ethical standards. SummitNext combined agile recruitment, database management, and quality validation to deliver a globally compliant dataset that strengthened the fairness and reliability of the client’s generative AI model.
Challenges
Uneven demographic representation in global AI training datasets.
Complex data collection logistics across India, China, Pakistan, Canada, and the US.
Stringent quality and compliance requirements with over 70 criteria.
Contributor hesitancy due to privacy and ethical concerns.
Solution:
SummitNext executed a three-phase model to deliver a diverse, high-quality dataset through agile sourcing and strict quality control.
- Freelancer Activation – SummitNext mobilized its internal pool of pre-verified contributors through trusted digital channels like Telegram and WhatsApp, ensuring rapid onboarding and diverse participant sourcing across five nations.
- Database Curation & Collection Management – All images were securely stored in a centralized database, categorized by gender, region, and skin tone. Real-time quota monitoring and metadata annotation ensured balanced representation and accuracy.
- Human-Centric Quality Control – A two-layer human review process validated each image for both technical precision and demographic accuracy. The project achieved 85% first-pass acceptance and 96% compliance, delivering a high-quality dataset aligned with the client’s standards.
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WHO WE ARE
We at SummitNext Technologies, founded in 2020, are a BPO company with a vision to transform customer support, customer acquisition, data annotation and backend support domains through technology, human expertise, and innovation. We are Head Quartered in Malaysia, with offices in Philippines. India and Uzbekistan. We are sup
ported with Remote teams in more than 28+ countries.
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