Predictive Analytics

We design predictive models that empower businesses to forecast trends, detect anomalies, and make data-driven decisions, from credit assessments to fraud detection.

Case Studies

Building a Mobile App for Sports Memorabilia Identification

The goal of this project was to develop a mobile app that could identify baseball cards from a database of cards using machine learning techniques. The app was designed to take a photograph of a baseball card and identify the card by matching it against a database of baseball cards. Once the matching was complete, all the metadata of the baseball card was returned to the user.

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Building an Interactive Dashboard for Net Zero Pathways

The goal of this project was to build an interactive dashboard for CO2 AI product, which helps companies measure, track, and reduce their environmental footprints at scale. The dashboard was designed to calculate Net Zero Pathways to achieve Net Zero Emissions (NZE) and provide real-time updates and results. The technology stack used in the project included Python, Pandas, Dash, Plotly, AWS S3, and AWS EC2.

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Deploying a Self-Service BI/Reporting Solution

This Company’s NOC Team in Pakistan was tasked with deploying a self-service BI/reporting solution for Telenor Pakistan's NOC. The goal was to provide up to 40 dashboards with drill-down functionality, representing different views of network KPIs, trends, and thresholds. The dashboards would aggregate data from various systems, including ITSM, IBM Netcool, WFM, and other systems in Company’s NOC IS/IT environment. The solution would also include some static data from Excel sheets and be viewable on a variety of devices.

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Flavor-Driven Food Recommendation System

A Machine Learning system that could predict the flavour of any food item and make recommendations for food and beverage pairings. The goal was to digitize and predict flavour using the flavour profiles of ingredients, recipes, and titles.

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Market Prediction Systems

An innovative market prediction system that leverages Thomson Reuters MarketPsych Indices (TRMI) to accurately predict daily movements of the S&P 500. The project involves a team of experts in finance, artificial intelligence, and machine learning who have used vast amounts of historical market data to develop a machine learning model capable of predicting future market movements

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Maximizing E-commerce Efficiency with AI/ML

An ecommerce platform that specializes in selling electronic and photonics components online. The company was seeking ways to streamline their operations and enhance the customer experience using artificial intelligence and machine learning.

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Medical Records Analysis for Insurance Claims and Malpractice Lawsuits

A comprehensive system that leverages machine learning models to analyze medical records and provide necessary insights to assess insurance claims and malpractice lawsuits. The system includes a dashboard that displays all the relevant information and predictions. The system architecture is built using AWS, which takes input from flat files stored in S3 and runs Lambda functions to finally display the analysis on QuickSight.

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Revolutionizing Surgical Preference Cards using Artificial Intelligence

Surgical procedures require precise instruments and consumables that are essential for successful outcomes. However, matching preference cards with inventory data is a time-consuming process that can lead to wastage of instruments and consumables, as well as the occurrence of "never events" - surgical errors that are preventable.

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Solar Proposals Automation

A system that leverages computer vision and deep learning to automate the creation of financeable proposals for residential solar installations. The system analyzes satellite imagery of residential rooftops, constructs 3D models of the rooftops and the trees and other obstacles around the rooftop, and uses energy usage information to create a solar installation design in an automated manner.

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