AI that works in production.
Human experts keep your AI accurate, reliable, and safe.
The Challenge:
Effective AI systems combine model capabilities with expert human oversight. Research on scalable oversight shows that human specialists working with AI substantially outperform both unaided humans and models alone. Building production AI requires this evaluation layer throughout the lifecycle: preference labeling for alignment training, systematic testing for model updates, and continuous monitoring for production quality.
Research Foundation:
Measuring Progress on Scalable Oversight (Anthropic, 2022)
Sweatshop Data is Over (2025)
Our Approach:
Expert evaluation teams that integrate directly into your ML pipelines. We execute preference labeling for RLHF training, systematic testing for model releases, and continuous production monitoring. You maintain control over evaluation frameworks while we provide trained capacity at scale. Built over ten years across Africa and globally.
Start with a free pilot.
Giovanni Campagna, ML Engineer, Bardeen.ai