Production-ready system by building and integrating scalable ML models
Built an agile and scalable cloud-based solution and ML model for digital consultants across countries and product categories to reduce their manual effort.
Business Challenges
The client is a leading cosmetics company and struggled with the existing system that wasn’t scalable. The absence of standard processes to access client resources like data sources, cloud machines, cluster environments, etc. made it challenging to create a production-ready system.
Sigmoid Solution
Sigmoid created a parallel set-up in the cloud and used Google Composer to manage workflow orchestration, ensuring the system has minimum manual intervention and better fault tolerance. We built and integrated scalable ML models to reduce manual effort and manage workflow orchestration better.
Business Impact
Our robust and scalable solution automated pipeline for ML model training and increased coverage for new countries, products and categories. This ensured the system has minimum manual Intervention and is easy to debug, extend and modularize, resulting in low maintenance and better fault tolerance.
Relevant Case Studies
ML-driven recommendation to power real-time sales analytics
ML-based demand forecasting solution to improve forecast accuracy while reducing costs by 5x
