Engineering Highlight Reel

Overseeing the Development of Key Products that Move the Needle

AI Engineered Applications

CHRWebAgent: Agentic AI Logistics Portal Automation

This project introduces CHRWebAgent, an innovative Agentic AI system designed for autonomous logistics portal automation. It intelligently navigates and interacts with web platforms to automate complex tasks like freight booking, tracking, and data entry, significantly reducing manual effort and enabling 24/7, error-free operational efficiency in dynamic logistics environments.

Document AI: Systematic Data Extraction Tool

This project developed a cutting-edge Agentic AI system that combines process agents with vision capabilities to automate systematic data extraction. It autonomously navigates web portals to find and download documents, precisely extracts data into a standardized format, and seamlessly updates internal enterprise systems, transforming manual data handling into an efficient, error-free, and scalable operation.

Generative AI for EDI

This project introduces a groundbreaking Generative AI system that empowers non-technical operations personnel to independently set up, map, and parse complex EDI documents. By abstracting technical complexities with natural language interfaces, it drastically reduces IT dependency, accelerates partner onboarding, and transforms EDI management into a self-service, agile capability.

Intelligent ETA Scheduling & Appointment Management

This project developed an intelligent automation system for Transportation Management Systems, streamlining real-time ETA calculations and optimizing appointment scheduling. By integrating dynamic data and predictive models, it eliminates manual overhead, significantly reducing operational costs, and enhancing communication and efficiency in complex logistics workflows.

Document OCR Data ETL, Government Trucking Contracts Portal Automation

This project developed an advanced ML system to automate the extraction and intelligent analysis of government trucking contracts. By leveraging OCR and robust ETL, the system efficiently scans portal data to proactively identify new business opportunities, predict renewal needs, and reveal strategic insights, significantly enhancing contract utilization and accelerating business development.

Machine Learning Applications

TMS Machine-Driven Automated Strategic Quoting

This project developed a sophisticated Machine Learning application that autonomously bids on trucking loads in auctions across various TMS portals. It leverages real-time data and predictive analytics to generate optimal strategic quotes, significantly boosting win rates and profitability while automating a complex, labor-intensive process.

ML-Driven Android OS Emulator as a Sales Generation Tool for e-Commerce Resellers

This project developed an ML-driven Android OS Emulator system that uses 20 synchronized virtual handsets to autonomously crawl mobile marketplace applications. It intelligently identifies and evaluates product listings, then automatically makes strategic offers to sellers, revolutionizing inventory acquisition and sales generation for an e-commerce reseller.

ML for e-Commerce: Unified Product Information Management System

This project developed an ML-driven Unified Product Information Management System designed for e-commerce companies to intelligently manage warehouse inventory. It leverages predictive analytics for demand forecasting and optimal stock level recommendations, drastically reducing stockouts and carrying costs while streamlining inventory operations for small to medium-sized businesses.

Automated Competitive Analysis Pricing Tool

This project developed an Automated Competitive Analysis Pricing Tool that crawls competitor websites for pricing data and intelligently adjusts internal product pricing. It then automatically re-prices products across our Magento e-commerce site, Google Shopping, and Amazon, ensuring real-time competitiveness, maximizing sales, and optimizing profit margins.

Reinforcement Learning Module for Google Shopping: Automated Strategic Pricing Optimization

This project developed a Reinforcement Learning Module for e-commerce, designed to autonomously monitor competitor pricing and adjust Google Shopping product SKUs. This system intelligently learns optimal pricing strategies in real-time, significantly boosting conversions, market share, and profitability by adapting dynamically to the competitive landscape.