Our projects

This project involves developing an AI-powered virtual assistant for PayPal using Google Dialogflow CX. The system handles customer queries through both chat and voice, enabling real-time support, faster issue resolution, and enhanced user satisfaction.

This project provides a configurable data pipeline solution under Honeywell’s Forge Insights. It offers a low-code interface for launching ETL jobs and data engineering tasks to drive performance and operational insights.

A smart data-driven project focused on insurance claims processing. It utilizes Python, Flask, OpenCV, GenAI, BigQuery, GCP, and PostgreSQL to analyze connected vehicle performance data. This cloud-deployed solution enhances claims adjudication using ETL pipelines, machine learning models, and accident-related analytics.

A logistics management platform built on Java Spring, MyBatis, and Oracle. It streamlines operations such as driver management, settlements, and delivery schedules, improving transportation workflows and visibility.

This telecom project supports network providers like Jio and Airtel by generating tabular and geospatial reports from raw flat file data. Built with Java, GWT, JavaScript, Kubernetes, Jenkins, it addresses production issues and ensures network analytics delivery.

Using Python and Data Science, this project segments users based on historical data to provide personalized product recommendations, boosting customer engagement and conversions.

Multiple solutions were developed for Mountain Leverage, including voice picking automation and ETL tools that optimize supply chains and fulfillment operations. Technologies used include Java, Spring Boot, and MySQL, aimed at improving productivity and worker safety.

A sustainability-focused initiative that leverages React, Redux, JavaScript, and .NET with Azure to facilitate green hydrogen production via renewable energy. It supports system integration, data visualization, and energy storage efficiency.

A web-based platform using Java, Maven, and Google Web Toolkit for electrical meter reading and energy usage tracking. It supports real-time monitoring and efficient data processing for smart energy decisions.

These projects involve monitoring IoT devices and visualizing sensor data. Built using Python, they capture real-time readings from flowmeters and provide actionable insights for industries like water management and automation.

Developed using Python, Spark, and AWS, this project integrates BVD data from Moody’s into SGA’s database, mapping it with BNYM’s entity structure for enhanced data analytics.