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Every year, SAP’s Internship Experience Project (SAP iXp) interns are invited to participate in the North America Hackathon. SAP iXp lines hiring with academic schedules, and intern cohorts in cities across North America partake in the event. Their Hackathon pitches are judged by regional SAP business leaders and subject matter experts.

If you’re not too familiar with what hackathons are, they usually span 24-hours and participants dedicate this time to ideation and creativity. Interns form teams and collaborate on inventive ideas, also known as “hacks.” The hacks can be anything related to a new business plan, product, app or solution.

Take a closer look at our winners and their incredible hacks:

Vancouver & North America Winner: Ali Serag El-din, Valerie Cheng, Himanshu Garg, John Yoo, Sam Moradi

Team Unyielding won not only the Vancouver Hackathon, but also took home the gold for overall SAP iXp North America Hackathon winner!

North America winning team, Team Unyielding: Ali Serag El-din, Valerie Cheng, Himanshu Garg, John Yoo, Sam Moradi

The Hack:

From Team Unyielding member Ali Serag El-din, Agile Developer, SAP

We’ve created a Short Message Service (SMS) platform that pushes out a message to those living in an area affected by a wildfire. We’ve specifically chosen SMS as our medium as it is readily available to most people and users don’t require a smartphone or mobile data to fill out a complicated form. SMS doesn’t jam up the phone lines and users don’t have to wait to connect—which is a common problem in these kinds of disasters.

The Solution:

We aim to make the process of immediate evacuation as well as finding a home to stay as simple as possible. A single SMS based platform for all our services such as accommodation, news updates and step-by-step directions.

We start by informing residents near the emergency of details about the areas affected. Those that live in the area are informed of the evacuation order and where to go, based on clear directions generated through the Google Maps Application Programming Interface (API), as well as advice on best practices concerning supplies. It then guides them through evacuation to safety.

Hack Roadmap:

In the future we’d also like to implement machine learning to accurately predict behaviors of forest fires in our text updates and preemptively inform them of steps to take. Our SMS service can be utilized by the Government of British Columbia as well as the Red Cross in efficiently helping rehouse and guide people affected by forest fires, and in the future, extend to aiding against all natural disasters.

Team Unyielding prototype

 

Bay Area Winner: Team Chippy: Anuj Singh, Jessica Kwon, Vishaal Prasad

From Team Chippy member Vishaal Prasad, Mobile Software Development Intern, TripIt

The Hack:

Our hack idea integrates open Yelp APIs into the TripIt app to allow our users to have a more personalized user experience. Users can input their interests into a TripIt profile, which then provides them with relevant suggestions for their trip.

The Solution:

Over time, TripIt would learn how a user travels and notice interests that a user may not have inputted into TripIt manually. Overall, this would lead to a higher customer stickiness as users would not have to leave TripIt to find activities and restaurants that are relevant to them. From a business perspective, a partnership with Yelp would benefit them as more users would likely be signing up for Yelp. Moreover, TripIt would receive a commission for users that sign up for a Yelp account from our app.

Hack Roadmap:

We came up with this idea when we noticed that partnerships such as those with Travel Companies and Airlines exist by leveraging the TripIt APIs that bring data in. However, we noticed that there was a lot of room for more partnerships by making use of APIs that bring data out.

Team Chippy hard at work

 

East Coast Winner: Team Aribros (Geoffrey Fowler, Max Rowan, Evan Verbus, Anthony Guerrieri, Matt Wessel)

From Team Aribros member Geoffrey Fowler, Procurement Operations Specialist, SAP Ariba

The Hack:

A high majority of [customer service] calls are repetitive issues such as creating an invoice. These are relatively simple walkthroughs, but this also means that more urgent calls are kept in queue for longer periods of time. I reached out to Max Rowan, a commerce SAP iXp intern that I worked with last year about using a chatbot as a customer service representative. We created our group and started pitching ideas.

The Solution:

The idea that we came up with was “SAP Otto” (the name is a spin on the fact that the chatbot is autonomous). What SAP Otto does is help customers with simple tasks such as creating an invoice or resetting their password by giving them step by step instruction via chat. Not only does this give the illusion of an actual Help Desk agent, but it allows those simple tasks to be taken out of the queue and the more complex issues to reach the Help Desk agents faster. It also has the potential to raise customer satisfaction, since call waiting time will be lower and have a greater return on investment due to Otto being software.

Team Aribros: Geoffrey Fowler, Max Rowan, Evan Verbus, Anthony Guerrieri, Matt Wessel

 

Bellevue Winner: Team LingoIt Pro: Congcong Li, Evan Adkins, Yan Luo, Kevin Ulrich

From Team LingoIt Pro member Yan Luo, Data Science Intern, Concur

The Hack:

The project was partially related to my intern project which is to build a language classifier, however I hadn’t planned to put it into a browser or a mobile app.

Currently, customers upload their photos of receipts taken on their phone to Concur for reimbursement. Concur uses OCR (optical character reader) to extract texts from images and later we can get the information we need from images, like amount and location. Now the OCR engine is somehow naïve since it tries to OCR every image in different languages one by one until it sees one which can give results making sense. Sometimes it gets the language wrong, especially for receipts in Asian languages. A language classifier can identify the language in advance and tell the OCR engine to run for a single time. This would save a lot of time for OCR and increase downstream analysis accuracy.

LingoIt Pro prototype

The Solution:

A faster OCR can make the waiting time of a customer much shorter and thus improve the user experience. It also means that we can increase our volume of receipt image processing and get ready for the expansion of customer base.

You can have a look at our demo video for some more details: https://drive.google.com/drive/folders/0B51wJAUisDEKWVJlUkZKNGpUdGc

Bellevue winners, team LingIt Pro: Kevin Ulrich, Evan Adkins,Yan Luo, Congcong Li

 

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