The Task
The client was building an AI-powered biometric system for banking terminals, designed to ensure secure customer authentication and payment processing through fingerprint recognition. To train and validate the underlying biometric algorithms, the project required a large, high-quality dataset consisting of 20,000 palm image sets.
Each set had to include six strictly standardized photos, three taken with the front camera and three with the camera on a mobile phone.
At this scale, broad geographic coverage and device diversity were also critical. At the same time, we had to keep the cost within a fixed budget, which turned the project into an exercise in precise traffic and workflow optimization.
The Solution
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Multi-platform strategy
We launched data collection across several international platforms. The main volume came from Prolific as it provides fast access to a global audience, high-quality responses and flexible participant filtering.
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Process organization and quality control
Even at high volume, attention to detail had to stay consistent at every step. We:
• created step-by-step instructions to ensure correct photo capture
• set up automatic format checks
• monitored diversity and representativeness
• controlled cost and collection speedThe goal was not only to gather photos, but to build a controlled and scalable process that would maintain quality at every stage.
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Audience management and filtering
Prolific’s filtering capabilities played a key role. They allowed us to:
• select participants with the right parameters
• keep upload quality consistently high
• maintain a stable and predictable data flowClear task structure and engaged respondents helped us deliver results ahead of schedule, roughly 10% faster than planned.
The Result
Collected 20,000 palm sets and launched the next batch of 20,000
Delivered a fully verified dataset ahead of schedule with consistently high quality
Scaled the process while keeping predictable speed and global coverage, with unified standards regardless of region, device or platform
