Case Study: M-KOPA transforms model management and compliance with Weights & Biases

M-KOPA Transforms Their Model Management Workflow with Weights & Biases

M-KOPA, a fintech company providing digital financing across sub-Saharan Africa, needed a better way to manage ML models in a highly regulated environment. Their team had been tracking experiments and production models in ad hoc notebooks, READMEs, spreadsheets, and manual processes, making it difficult to maintain compliance, auditability, lineage, and collaboration across data science, product, and business stakeholders. They used Weights & Biases Model Registry to create a centralized model management hub and single source of truth.

With Weights & Biases, M-KOPA streamlined model promotion using Protected Aliases, RBAC, and Action History to clearly track staging, QA, challenger, and production versions. The solution improved governance, reduced manual error, strengthened audit trails, and made it easier for non-technical stakeholders to participate in deployment decisions. While no hard metrics were provided, M-KOPA reported faster, more seamless workflows and better trust in their model management process thanks to Weights & Biases.

M-KOPA

Benedict Eugine

Data Scientist