AI-Powered Inventory Management

What Challenge Did E-commerce Retailer Face?

A major e-commerce retailer was losing millions to stockouts and overstock situations. They needed an intelligent system to predict demand across 100,000+ SKUs and automate reordering.

How Did Agochar Approach This Project?

We began with a comprehensive discovery phase to understand the client's needs, existing infrastructure, and future goals. Our team developed a detailed technical architecture that would address current challenges while providing flexibility for future growth.

• Conducted stakeholder interviews and requirement gathering
• Analyzed existing systems and identified integration points
• Designed scalable architecture using modern best practices
• Implemented iterative development with continuous feedback

What Solution Did Agochar Build?

We developed a machine learning pipeline using Python and TensorFlow for demand forecasting. The system analyzed historical sales, seasonality, promotions, and external factors. Integration with their ERP enabled automated purchase orders.

How Was the Project Implemented?

Our development process followed agile methodology with two-week sprints and regular client demonstrations. We maintained close communication throughout the project to ensure alignment with business objectives.

1. Phase 1: Foundation and core functionality
2. Phase 2: Feature development and integrations
3. Phase 3: Testing, optimization, and launch preparation
4. Phase 4: Launch and ongoing support

What Was the Business Impact?

The project delivered significant measurable results for our client. The new system has transformed their operations and positioned them for continued growth in their market.