Wildebeest

For Wildebeest

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Overview

$50,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

2 - 9

Employees

2014

Year Founded

ABOUT WILDEBEEST

Exceptional software built by caring humans

Wildebeest's top teams enhance great software. We focus on understanding our clients' perspectives to create tailored, innovative solutions for every challenge. We're currently welcoming clients who need a dedicated development team for ongoing support or, in some instances, project-based engagements. If this applies to you, we would be eager to connect. Our consultancy, established in 2014 by Ran Craycraft and Kevin Ng, is centered on custom software development with a focus on products and platforms. Over the years, we've assisted hundreds of businesses in achieving their objectives more swiftly while earning various awards and industry accolades by adhering to our core belief: Software is the most powerful medium in the world. It serves as both our tool and our muse for developing transformative products that empower individuals.

Tech Stack

Amazon Application Development FrameworkGoogle app engineAirtableNodeJSReactJavaScriptTypescriptPHPPythonRedux

Languages Spoken

English

HIGHLIGHTS

$50,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

2 - 9

Employees

2014

Year Founded

Services

Focus

Industries

Clients

Services Provided

25% Custom Web Application Development

15% Mobile App Development (iOS & Android)

10% E-Commerce Development

18% Product UX Strategy

15% UX Research & Usability Testing

12% Web App UI Design

5% Landing Page Design

Portfolio

CheetleID: AR Cheetle Detection Web App

Frito-Lay

You know that orange residue on your fingers after enjoying Cheetos®? It's referred to as "Cheetle." We collaborated with Frito-Lay to create an augmented reality, web-based Cheetle detector, which we launched during Super Bowl LIV. The concept was to develop an app that could identify if someone had recently eaten Cheetos. If it confirmed this, users would unlock exclusive behind-the-scenes content from the Super Bowl commercial. We faced a tight deadline, with only about four weeks to design and develop an app capable of detecting Cheetle on hands. There were numerous challenges, including ensuring our detector worked for hands of all shapes, colors, and sizes. We also needed to prevent users from sharing inappropriate images. Given the high viewership of the Super Bowl, we had to ensure the app could handle significant traffic. We created a machine learning model to confirm that a hand was present in the photo, and then enlisted friends across the country to eat large quantities of Cheetos and send us photos of their Cheetle-covered fingers (definitely an odd text to send). We ended up with tens of thousands of images of orange-stained fingers. We had considerable influence over the user experience design, and our client allowed some leeway with their brand guidelines. Ultimately, we developed a mobile-first web app using Next.js, which loads quickly and scales effectively with the Google Cloud.

Know Your Data: ML Predicting March Madness

NCAA & Google

Every March, basketball enthusiasts nationwide come together to support their alma maters as they aim for the Final Four®. To showcase the impressive computing capabilities of Google Cloud, we collaborated with Google and the NCAA to develop a predictive web application. Our task was to swiftly design and create a real-time dashboard that would display machine learning predictions along with their accuracy. We had just over a month to ideate, design, and build this platform. Additionally, we needed to find a secure method for non-technical content creators to manage the content without using a traditional CMS. Our approach involved utilizing Google App Engine (Python) and AngularJS to create a web app that utilized live data from Firebase. While content management was necessary, the restriction on CMS for security reasons prompted us to develop a text editor powered by Google Sheets, allowing our clients to submit their editorial predictions, which we then exported as JSON for upload to Firebase. As the games unfolded, our interactive infographics updated in real-time, showcasing predictions with over 80% accuracy. This initiative ultimately earned a Gold award at the 2019 Cannes Lions in the Creative Data: Best Use of Real-Time Data category.

Augmented Reality Damage Detection App

Cox Automotive

A prominent automotive brand was introduced to us by our contacts at Google, with the task of exploring how artificial intelligence could be utilized to assess vehicle damage. Our objective was to create an augmented reality mobile application capable of scanning vehicle damage and providing repair or replacement cost estimates. Furthermore, our client asked for a 3D design of a portable controlled environment that could employ advanced technologies for more accurate damage assessment. The project presented numerous challenges, the most significant being the need to identify damage on vehicles of varied shapes and sizes. Although our client possessed a substantial amount of data (photos of damaged vehicles), there was minimal standardization, and the images were predominantly low resolution. We developed a hybrid React Native mobile app that first scans the VIN to identify the vehicle’s make, model, and year. The user is then prompted to scan the vehicle's exterior to identify any visible damage. If damage is found, our machine learning model assesses both its severity and specific location on the vehicle. Based on the make, model, year, severity of the damage, and its location, the app determines whether the dent, scratch, or scuff can be repaired or requires replacement. Finally, we provide a score for the vehicle along with an estimated cost for the repairs.

3 more projects