Business Objective
ABC Mart, a fast-growing organic food manufacturer operating in India and New Jersey, faced inefficiencies in managing supermarket order data, affecting inventory planning and customer satisfaction. To address this, we designed a cross-border supply chain automation system to centralize, clean, and analyze order data from multiple geographies using AI and agentic tools.
Problem Statement
The operations team discovered major discrepancies in inventory visibility and fulfillment timelines due to fragmented order data flowing in via emails from USA and India supermarkets. These gaps made it difficult to maintain optimum inventory levels and fulfill orders on time, threatening customer relationships and scalability.
Solution Architecture
Agentic Automation with n8n
Set up a fully automated workflow using n8n to monitor country-specific Gmail inboxes, extract attached CSV files, parse order data, and push it into a PostgreSQL database for unified access.
PostgreSQL Data Layer
Structured the incoming data into fact and dimension tables for orders, products, and customers.
AI Spreadsheet via Quadratic
Connected PostgreSQL to Quadratic AI to run analysis in an AI-powered spreadsheet. Created date and exchange rate tables, merged cleaned data, calculated order values in INR, and engineered KPIs like OTIF%, Fill Rates, and On-time Delivery.
Key Metrics Tracked
Order Fulfillment KPIs
OTIF %, On-Time %, In-Full %, Volume & Line Fill Rates.
Customer Insights
Top 5 customers by order value across US and India, mapped with city, OTIF %, and delivery metrics.
Financials
USD to INR exchange rate adjustments, and total order amount calculations in INR.
Automation Flow Diagram
Conclusion
Developed a scalable, agentic automation pipeline that integrated emails, databases, and AI spreadsheets to automate supply chain reporting. Improved data reliability, increased visibility across borders, and enabled proactive inventory decisions. Positioned ABC Mart for faster geographic expansion with data-driven logistics.