Use Cases
Sales Forecasting - Global Packaging Giant
Sales forecasting was carried out by analyzing potential business from existing and new customers, by understanding business growth, hard churn, soft churn (decline in revenue) and conversion.
Improving DIFOT – Global Manufacturing Firm
With an accuracy of 87%, for SKUs/ Parts, predicted DIFOT (Delivery in full on time) & helped improve it by understanding reasons, by considering factors such Demand Forecasting, Inventory Management, Lead times etc.
Global Logistics & Shipping Firm
Helped identify which shipments suffer from delays and why so, thereby allowing the global giant to take remedial actions about improving the on-time delivery of the shipments for its customers in multiple geographies.
Why Choose
EazyML?
EazyML is an enterprise-grade AutoML platform that accelerates the journey from data to deployed models by simplifying model development, deployment, and lifecycle management.
With built-in governance and explainability, EazyML enables enterprises to scale AI confidently across pricing, customer experience, operations, and risk sensitive use cases.
Automate feature engineering, model selection, and tuning to dramatically reduce time from data to production-ready models.
Deploy, manage, and monitor models across environments with support for continuous learning, versioning, and performance tracking.
Built-in explainability, model monitoring, auditability, and controls ensure AI decisions remain transparent, trusted, and compliant.
EazyML serves as the underlying AI backbone powering platforms like GCC Suite and Price-It-On®, enabling consistent, reusable intelligence across solutions.
Key Features
EazyML delivers an enterprise AutoML framework covering data preparation, feature engineering, model training, deployment, monitoring, and governance. It enables scalable, explainable AI execution across diverse business use cases while ensuring control, reliability, and lifecycle management.
01
Automated Model Development
Automates feature engineering, algorithm selection, and hyperparameter tuning to rapidly generate high performing models with minimal manual effort.
02
Explainability & Transparency
Built-in explainability helps teams understand model drivers, validate decisions, and build trust with business users, auditors, and regulators.
03
Deployment & Continuous Monitoring
Deploy models into production and continuously monitor performance, drift, and stability across environments and use cases.
04
Governance & Lifecycle Management
Manage model versions, approvals, audits, and retraining workflows with enterprise-grade controls to ensure compliance and reliability.
05
Enterprise Integration & Reusability
Integrate seamlessly with enterprise data, cloud, and application ecosystems, enabling reusable models and consistent AI capabilities across platforms and solutions.
How It Works
Discover
Identify key supply chain inefficiencies and risks.
Ingest
Collect and structure procurement, and inventory data from multiple sources.
Understand
AI models detect patterns in demand, supplier risks, and disruptions.
Gain Insight
Predict optimal procurement, demand, and inventory decisions.
Act
Automate real-time supply chain adjustments for maximum efficiency.
Embed
Operationalize AI-driven supply chain intelligence into existing enterprise systems.
Accurate demand forecasting is crucial
→ "With continuous market shifts, an accurate demand forecast prevents overstocking, stockouts, and lost revenue opportunities."
Optimizing Procurement, Inventory, and Logistics
→ "Supply chain costs represent one of the largest expenses for most companies. AI ensures procurement, logistics, and inventory management are continuously optimized for cost efficiency."
Supply Chain Intelligence Powers Growth
→ "Agile supply chains drive higher profitability and faster response times. AI-driven insights ensure strategic decision-making across procurement, manufacturing, and logistics."
Best-in-class supply chain insights excellence requires:
Scale & Complexity: Manage global supply chains efficiently by analyzing supplier, demand, and logistics data at scale.
Velocity: Respond to supply chain disruptions in real-time with AI-driven decision-making.
AI-Driven Recommendations: AI identifies optimal sourcing, logistics, and procurement decisions to minimize risks and costs.
Productivity Enhancements: Automate procurement, forecasting, and supplier negotiations to free up teams for strategic decision-making.
Importance of Supply Chain Insights
A well-optimized supply chain is critical for profitability and business success.
With complex global networks, fluctuating demand, and increasing supply chain disruptions, businesses must leverage real-time AI-driven insights to maintain efficiency and resilience.
