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TEAM LGTM

Anushrut Pandit

Arnab Bhowmik

Om Dwivedi

Om Lanke

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SaaS

Platform

Hyperlocal has taken off in India, but demand prediction remains a challenge. Can AI help with inventory management?

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AI Powered Inventory Management Tool

Overview

AI-powered solution for hyperlocal demand forecasting and inventory management
Tailored to address challenges in India’s hyperlocal market
Provides data-driven insights and automation
Supports retailers in stock management, product sourcing, and delivery optimization

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Inventory Management

Efficient inventory management is central to ensuring customer satisfaction and minimizing stock-related losses. With the rapid changes in consumer demand in hyperlocal markets, our AI-powered solution will incorporate the following features to enhance stock control, optimize supply chains, and forecast demand:

AI-Based Suggestions on Forecasted Demand

AI algorithms will assess past sales data, local demand trends, and seasonal variances to provide stock suggestions. By identifying top-selling items and estimating future demand

Emergency Level-Based Suggestions

Our platform will monitor emergency inventory levels, alerting managers when specific items run low or experience surges in demand.

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Vendor Integration and Ordering with Local Suppliers

A key feature is connecting businesses with local vendors (e.g., kiranawalas). This integration will allow businesses to source items locally, enabling rapid replenishment and mitigating stockouts. By automating vendor selection and ordering processes, our system can make local procurement highly efficient

Sales and Inventory Updates via Excel/CSV Import (Drag-and-Drop)

To make data integration simple, the platform will support drag-and-drop importing of sales and inventory updates from Excel or CSV files.

Hit/Miss Ratio Analysis and AI Summary

If selected, an analysis of the Hit/Miss Ratio will provide insights into forecasting accuracy, allowing businesses to adjust their strategies accordingly

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Demand Forecasting

Reliable demand forecasting is essential to ensure products are stocked according to local demand patterns. Our AI model will integrate various data points, such as historical sales data, market trends, and external factors

Weekly Demand Predictions

The platform will analyze weekly demand data, identifying patterns and projecting future needs. This analysis will allow retailers to adjust their stock levels dynamically, reducing both shortages and excess inventory.

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Event-Driven Adjustments�By incorporating holiday schedules, seasonal changes, and local events, the system can better anticipate demand spikes or lulls. This foresight will improve customer service levels while keeping inventory costs in check.

AI-Adaptive Model�Our demand forecasting model will improve over time through machine learning, learning from each forecast cycle to refine its accuracy. The adaptive AI will allow our model to adjust its predictions in response to changing market trends.

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