Sanofi Financial Data Forecasting Intelligence System

Sanofi required an end-to-end architecture to enable AI-based financial forecasting across the enterprise for the FP&A (Financial Planning & Analysis) team. Key challenges included: Aggregating large-scale financial data from multiple sources Establishing a reliable and reproducible ML training and evaluation workflow Ensuring scalability, accuracy, and robustness of forecasting pipelines Building a future-proof foundation aligned with industry best practices in data and MLOps

OrbitaLab designed and implemented a comprehensive Data & ML architecture covering the full forecasting lifecycle: Cloud-native data ingestion and aggregation on AWS with centralized analytics in Snowflake ML lifecycle management using MLflow for experiment tracking and model versioning Automated forecasting workflows built in Python Containerized services deployed on ECS (instead of EC2) Infrastructure as Code with Terraform and CI/CD managed via GitHub