Expert teams for production AI.
Keeping your AI accurate, reliable, and safe.
The Challenge:
Expert humans working with AI tools substantially outperform AI alone arxiv. Progress now requires deep expertise and sustained context, not commodity labeling mechanize. ML engineers are frequently allocated to evaluation workflows when their time is better spent on model development and architecture.
Research Foundation:
Measuring Progress on Scalable Oversight (Anthropic, 2022)
Sweatshop Data is Over (2025)
Our Approach:
Expert evaluation teams developed over a decade across Africa's top tech hubs and globally. We execute your evaluation frameworks for preference data creation, regression testing, and production monitoring at a fraction of enterprise costs, enabling your engineers to focus on core model development.
Data Security:
Client data processed in isolated environments with 24/7 SOC monitoring. Hardened endpoints or managed VDI with encrypted storage, VPN-enforced connectivity, and least-privilege access.
Configurable retention policies and documented incident response. Security program managed by certified professionals with regular third-party audits.
Start with a free pilot.
Giovanni Campagna, ML Engineer, Bardeen.ai