Africa’s Most Deployment-Ready Annotation Workforce

In this track, you learn how real KYC and banking operations work behind the scenes. You’ll verify IDs and official documents—passports, NIN, driver’s licenses, voter cards—then validate OCR outputs and correct machine-extracted data so systems stay clean and audit-ready. 

You’ll tag personal and sensitive information (PII) properly, label fraud patterns and risk indicators, and learn to work within NDPR/GDPR and CBN-aligned KYC rules. By the end, you’re not just clicking boxes—you’re thinking like a compliance-aware operator inside a modern financial institution..

This track drops you into the world of claims and risk. You’ll interpret insurance claims across motor, health, property, and liability, then annotate damage on vehicles and property using bounding boxes, polygons, and segmentation that models can actually learn from.

 You’ll classify underwriting data, assign risk categories, and work with multimodal claims inputs—photos, adjuster reports, repair estimates, and claim forms. You’ll also learn to tag fraud patterns and suspicious claims, helping automate decision-making while keeping human-level judgment in the loop.

Here, you step directly into the frontier of AI. You’ll learn to classify text by sentiment, intent, topics, and entities; perform RLHF by ranking model responses, spotting hallucinations, and scoring quality; and detect bias, toxicity, and unsafe or unethical outputs before they reach users. 

You’ll evaluate summarization, translation, creativity, and instruction-following, and build a practical understanding of prompt behavior and model limitations. This track is for people who want to sit at the intersection of AI quality, safety, and human judgment.