Oversaw the complete implementation of an ERP and POS system for a book store, ensuring seamless integration and customization of various business modules. This included Inventory Management, Point-of-Sale (POS), Finance and Accounting, Human Resources (HR), Business Intelligence (BI) Reporting, E-commerce Integration, Warehouse Management, Order to Cash, Purchase to Pay, and Production. Partnered with stakeholders to gather requirements and convert them into actionable technical specifications. Enhanced the ERP with custom features to boost operational efficiency and streamline business workflows. Conducted extensive software testing to confirm high-quality outcomes and provided comprehensive user training and support for smooth adoption.

Integrate OpenAI with ERPNext to enable natural language queries, allowing you to quickly access real-time data from the ERP system’s database and gather all the necessary information in one place.

The UCO Pickup mobile app streamlines the collection of used cooking oil (UCO) from FBOs by collection executives. Key features include Bluetooth integration for weighing machines, GRN generation, vehicle tracking, route management, and FBO self-enrollment with verification. The app also enables UCO requests, rescheduling of collections, and detailed reporting for efficient monitoring and follow-ups. It ensures smooth coordination between FBOs, BDEs, DEOs, and collection executives, while providing real-time data on oil collections and deposits.

This module enables seamless integration with Axis for processing payments in ERPNext. It allows businesses to make payments and receive funds from business partners directly within the ERP system. The integration streamlines financial transactions, ensuring efficient payment out and payment receipt processes, while maintaining accurate records for smoother business operations.

Associated with JNTUH College of Engineering Hyderabad (Aug 2022 - Nov 2022) This project focused on developing a Volume Control System utilizing Hand Recognition Technology. The primary goal was to design a system capable of recognizing hand gestures through a pattern recognition approach, leveraging histograms of local orientation for accurate detection. The system was developed to be straightforward and did not require specialized hardware beyond a standard workstation or PC. Image digitization was facilitated through common devices such as scanners or digital cameras. The outcome was a user-friendly, gesture-based volume control system that provided an intuitive way for users to adjust volume levels seamlessly.