Amazon, the largest online retailer in North America, sells a large variety of products. After a sale, customers may post reviews related to all aspects of the sale. On average, users write millions of reviews per year.

With the large number of reviews posted, the likelihood that customers encounter reviews unrelated to product quality is high. Without an automated way of classifying reviews, customers may have to sift through many useless reviews when researching a big-ticket item.

Our Amazon Customer Review Analyzer, ACRA, automatically classifies customer reviews into two categories, those related to product quality and those unrelated to product quality. To do so, ACRA uses natural language processing and machine learning.

This automatic classification of reviews allows Amazon shoppers to focus only on reviews that are relevant to product quality, thereby enhancing their shopping experience.

Amazon shoppers can search for products using our ACRA iPhone app, which separates reviews into product quality and non-product quality categories. Additionally, users can report misclassified reviews to refine and crowdsource our classifier’s performance.

Our iPhone application is written in Swift and communicates with our backend using API Gateway and Lambda hosted on Amazon Web Services (AWS). Amazon Machine Learning and Python’s NLTK library are used to classify reviews hosted in AWS’s S3 and DynamoDB.

Founded in 1908 and headquartered in Detroit, General Motors designs and manufactures a wide variety of vehicles that meet the needs and expectations of drivers around the globe. With a passion to earn customers for life, GM is always working to improve their driving experience.

The GM Technical Center, located in Warren, Michigan, is the heart of the company’s engineering effort. Consisting of 38 buildings and housing over 21,000 employees, the campus spans 710 acres.

Our GM Transportation Experience App is designed to ease the stress that comes with navigating the large GM Technical Center campus by guiding drivers to a parking lot with open spaces that is near their destination.

After a user selects a building destination, our app finds the parking lots within the proximity of that building and analyzes historical data associated with those lots to determine which lot has the highest chance of containing an open parking spot. The user is then directed to this lot via Google Maps.

Since our app is intended for use primarily while driving, a key component to its design is simplicity. Users enter their destination building before driving. While driving, our app guides them with voice prompts to the best parking lot for their building destination on the GM Technical Center campus.

Written using Xamarin, the GM Transportation Experience mobile application runs on both Apple iPhones (iOS) and Google Android devices.

Humana provides many innovative products, services and business practices that help consumers make healthcare decisions with confidence.

As one of its goals, Humana aims to improve the health of their members by 20%. With childhood obesity doubling in children and quadrupling in adolescents, there is a need to counteract the recent growth of unhealthy lifestyles.

Our Humana Kids Android mobile app educates children and parents about nutrition and exercise through a series of pop-up surveys, tips and challenges that promote healthy living.

Humana Kids allows parents to switch our app to “Child Mode” in which health and exercise related pop-ups appear while their child uses their device. To incentivize children to make healthy choices, coins and badges are awarded for positive responses on surveys, which determine their ranking compared to other users.

Parents view their child’s health trends through our companion web app. Graphs generated from their child’s responses visualize the current results. Parents receive tips tailored to their child to promote further healthy choices.

Humana administrators use our companion web app to view graphs displaying general health trends of all users. Humana administrators can modify and add surveys, tips and recipes.

Our mobile app is written in Java and runs on any Android device. Our web app is written in Python and utilizes the Django framework. Both are interfaced with a REST API connected to a SQLite database.

Meijer is a large supercenter chain located in the Midwest. With over 200 stores, Meijer is one of the largest retailers and private companies in the nation.

Our MyMeijer Crowdsource Shopping mobile app improves the shopping experience at Meijer stores by enabling customers to report potential issues within the store to Meijer team members immediately so they can be resolved quickly. Issues may include out-of-stock merchandise, spills or any other hazards.

Customers use Meijer’s mPerks loyalty program to save money by redeeming digital coupons and rewards. Customers can now earn mPerks points toward rewards by using our MyMeijer app to report issues while shopping.

Meijer in-store team members use our companion Bluebird mobile app to respond quickly to push notifications sent to them by our system about issues noticed by shoppers.

All reported issues and resolutions are logged in a central Meijer database. Meijer managers use our companion Corporate Scoreboard app to detect frequently out-of-stock items and issues at Meijer stores across the country. It displays statistics collected from the customer reports, which assist Meijer management in running their stores efficiently.

Our MyMeijer Crowdsource Shopping system is written using Xamarin. The customer app runs on Apple (iOS) and Google Android devices; the Meijer team member app runs on Windows. The Corporate Scoreboard web app is written using .NET framework and hosted on Azure Cloud Services.

Michigan State University has one of the largest campuses in the nation, with more than 500 buildings on 5,000 acres. The Capital Area Transportation Authority (CATA) is the public transit service that services both Michigan State University and the greater Lansing area.

With over 30 routes, the CATA bus system is complex. Our mobile app CATAlyst enables riders using CATA to navigate the bus system easily and to arrive at their destination on time.

CATAlyst users select and view bus routes integrated within Google Maps. They can view all buses moving in real-time and all stops on a particular route. The arrival time of the next bus is displayed simply by selecting a specific stop.

Users can create and save weekly scheduled trips for classes and other events. CATAlyst maps out the best routes for a trip based on all available routes and the time of day.

CATAlyst sends a push notification to a user’s mobile phone, notifying them when to leave for a scheduled trip. The push notification includes the time it takes to walk to a specific bus stop from their starting location and the total estimated trip time.

CATAlyst is a mobile app written in Swift for Apple iPhones (iOS) and Java for Google Android phones using CATA real-time data. The server side utilizes RESTful APIs written in Java, using Maven and Spring Boot on an Ubuntu 16.04 Server with a MySQL database.

Headquartered in Redmond, Washington, Microsoft is one of the largest software and hardware companies in the country. They are leaders and innovators in all areas of technology.

Microsoft’s Intune provides mobile device management, mobile application management and PC management capabilities from the cloud. Using Intune, organizations can provide their employees with access to corporate applications, data and resources from virtually anywhere on almost any device, while helping to keep corporate information secure.

Our Intune Company Portal Helper Bot is an automatic chat bot that interacts with users when they experience problems inside the Microsoft Intune Company Portal app, which connects to Microsoft’s internal Intune mobile management system.

As the Intune user base grows, the need to assist individual users experiencing issues grows as well. To help meet this increasing demand, our helper bot provides automated real- time help to Intune users to resolve their problems.

Users ask our bot questions related to their issue. Our bot searches through its curated database of documents to find articles related to the user’s problem. The bot sends the articles it finds to the user for review.

If our helper bot is unable to find an article that resolves the user’s issue, the user can submit a bug report for the Microsoft Intune Company Portal team to investigate further.

Our bot is written using .NET, Java and Microsoft’s Bot Framework. The app runs on Android devices and is deployed using Microsoft Azure cloud services.

Founded in 1937, Michigan State University Federal Credit Union offers financial services to Michigan State University and Oakland University faculty, staff, students, alumni association members and their families. With 230,000 members and over $3.3 billion in assets, MSUFCU is the largest university-based credit union in the world.

MSUFCU currently offers mobile banking apps on both Apple (iOS) and Google Android devices for members to access their funds and perform banking transactions at any time.

Our Banking with Amazon’s Alexa and Apple’s Siri systems maintain MSUFCU’s technological edge by expanding their banking offerings to voice-controlled smart devices such as Amazon Alexa-enabled devices, Apple Watch and Android Wear.

Voice-controlled technologies give MSUFCU members new ways to interact with their accounts, including accessing their account balance, transferring money and obtaining information about recent transactions. Members can request other information about MSUFCU such as branch hours, current loan rates and the location of the nearest ATM or Branch.

Our companion administrative web portal enables MSUFCU staff to manage the available information and services offered by these voice technologies. Frequently asked questions can be added to the apps in minutes to improve the user experience.

The Alexa skill is written in Python, Apple Watch in Swift and Android Wear in Java. All three contact a MySQL database through JSON. The administrative web portal is written in PHP.

Rook Security, based in Indianapolis, Indiana, is a managed threat response force that is dedicated to providing global IT security solutions that anticipate, manage and eliminate threats.

As the number and types of devices connected to the Internet increase, the need to protect those devices from attackers is increasing as well.

To this end, Rook Security provides their Force platform, which is a tool that streamlines the process of handling incoming security alerts, thereby increasing the efficiency of Rook’s in-house security analysts and lowering response times to threats.

Our Force Platform Ingestion Tool with Alert Correlation system is a tool that processes security alerts from Rook clients for ingestion into the Force platform.

When a security alert is received by the Force platform, our system processes the alert by extracting key information and by analyzing the alert to determine whether it relates to other recent alerts, potentially grouping it into a larger case automatically.

Rook security analysts view these security alerts and respond accordingly depending on the type of attack, the source of the threat, the threat level and other relevant information.

Our system also enables Rook analysts to create connections with new clients to route their alerts into Force to be monitored.

Our Force Platform Ingestion Tool with Alert Correlation system runs on a Python Django web platform, using React/ Redux JavaScript libraries, and is accessible by any modern web browser.

Spectrum Health provides high quality healthcare in Western Michigan through 10 hospitals, 7 urgent care centers and 33 laboratories. Together, Spectrum Health employs nearly 3,100 physicians, residents and advanced practitioners.

After graduating from medical school, physicians train for a number of years as resident physicians at hospitals before becoming certified in their field of specialty.

Hospital resident physicians are limited by federal regulations in the number of hours they may work in a single shift, so they must keep track of their shift times accurately.

Resident physicians click the Start button on our mobile app to begin their shift. Push notifications alert the resident if they are approaching a shift time limit per federal regulations. Clocking out is as simple as pressing the Stop button. Our app provides for manual time entry if the resident forgets to start or end their shift.

Administrators called Resident Coordinators use our companion web app to manage groups of residents. Resident Coordinators can view clock-in and out times, see shift data by resident, and select a date range for the shift display. An Export button exports data for importing into Excel.

Our Resident Physician Tracking system utilizes Swift for Apple (iOS) devices and Java for Google Android devices. It uses ASP.NET Core MVC with .NET Core and Entity Framework for its API.

Union Pacific is a leading transportation company headquartered in Omaha, Nebraska. Union Pacific has over 8,500 locomotives running on 32,100 miles of track across 23 states with over 44,500 employees.

When Union Pacific assigns an engineer or conductor to a new train route, they must learn the new route by riding along on a train with another engineer or conductor who already knows the route. This process can take days for each new train route to be learned, resulting in millions of dollars spent annually as multiple engineers and conductors learn multiple routes.

Our Learning New Train Routes system is an augmented reality software that uses actual video of the train route taken by cameras mounted on engines. Our software overlays this video with important information including mile markers, train speed and important landmarks such as signals and switches.

Engineers and conductors use our companion web app to view an augmented reality video of a new train route. They can view videos from anywhere, at any time, and on any web- browsing device.

A Google Maps display shows the train’s progress along the route. Engineers and conductors can move around in the video by clicking on the map. In particular, they can replay sections of track to ensure that they learn the new train route well.

Our Learning New Train Routes system is written in Python and utilizes OpenCV and Darknet for image recognition. HTML, CSS and JavaScript are used for the web app.