Client: Mid-Sized Automotive Parts Manufacturer (India)Industry: Manufacturing & Industrial AutomationLocation: Pune, IndiaServices Deployed: AI/ML Development, Predictive Maintenance, Computer Vision, Forecast Modeling, Digital Twin SimulationTech Stack: Python, TensorFlow, OpenCV, AWS, MQTT, PLC Integration, React (Dashboard) 📌 Client Overview The client
📌 Client Overview A mid-sized renewable energy company operating across India, managing wind and solar farms with over 10,000 customers, 200+ field engineers, and multiple regional offices. 🎯 Problem Statement The client faced complex challenges: The need for a
Background The client operated a legacy on-premises billing system handling sensitive customer data, meter readings, invoices, and payments. With growing data volume, remote work trends, and increasing regulatory demands, the company sought to modernize their billing infrastructure. However, fully
Introduction Search engines and recommendation systems form the backbone of user interaction across platforms such as e-commerce, job portals, social media, and enterprise solutions. The ability to effectively match a user’s search intent with relevant information is crucial. Traditional
1. Introduction As data volumes grow exponentially, businesses require sophisticated analytics tools to visualize insights effectively. Techavtar developed an AI-powered data analytics system to automate graph creation and pattern detection from large datasets, enabling data-driven decision-making. 2. Objectives 3.
1. Introduction With the growing demand for quick and accurate food product searches in e-commerce and retail, leveraging AI-driven database optimization and automated model training has become imperative. This case study explores how AI enhances database management and search
