04 Mar Case Study: Mobile Applications and Machine Learning Projects
Akvelon has developed and designed mobile applications for several clients across industries including Smartsheet, WebMD, Lookout, Linkedin, Indemand Interpretting, T-Mobile, and On Semiconductor. Akvelon developers have also utilized Machine Learning and AI to complete projects for clients across industries as well.
From telecommunications to medicine, companies from every industry are in need of assistance to design and develop their mobile and web applications, and many turn to Akvelon for their expertise and years of experience. When it comes to Machine Learning and AI, many companies don’t even know where to begin with these emerging technologies. That’s where Akvelon comes in, utilizing Machine Learning and AI to provide solutions that optimize the company’s processes better than ever before.
Mobile App Projects
Smartsheet is a leading Software as a Service (SaaS) company who offers an enterprise-ready Cloud app for work management and collaboration. Smartsheet is used by over 50% of Fortune 500 companies. Akvelon worked on the Smartsheet iPhone/iPad & Android automated testing system, reducing testing costs, the number of hours and testers involved in a project, and the time taken for regression testing when new features are implemented.\
WebMD app “Wellness at Your Side” is fully integrated with WedMD’s online portal, this app lets you set lifestyle goals, track your progress, earn rewards, message a coach, and get personalized well-being recommendations. Akvelon created the new version of the application, introducing new UX, animations, navigation, adding new features such as steps counter integration, SSO, TouchID, User Profile, Custom Card containers, optimizing performance.
Lookout is a global leader in protecting mobile data, privacy, and security. Akvelon delivered several major product features, such as Identity Protection, SSN Watch, Social Media Watch, and AT&T Smart Networks. Akvelon also supported Lookout partner versions for carriers in North America, Europe, and APAC.
LinkedIn needed to create superior quality in its applications in a very rapid release cycle. Prior to involvement of the Akvelon team, all testing was done manually, consuming large amounts of time and producing more errors. Akvelon developed a modular, extendable, and reliable automated test framework. LinkedIn was provided with two powerful automated testing systems to check the LinkedIn mobile client application for both Android and iOS.
InDemand Interpretting application makes it easy to access high quality, medical interpreting on your iOS mobile device. Akvelon team worked to develop parts of the architecture of the app and to maintain and implement a third-party widget (Angular) and Rest API.
T-Mobile Akvelon worked with T-Mobile to develop apps such as T-Secure, My Account, Bonus Apps, and more. T-Secure utilizes both static and dynamic analysis, scanning any android application for malicious activities. T-Mobile My Account is the easiest and fastest way to connect with T-Mobile on your phone. Bonus Apps is a widget that makes it easier for T-Mobile customers to see what Applications are available for their specific device.
On Semiconductor (formerly known as Aptina) designs and manufactures some of the most advanced CCD chips employed in most cameras and phones. For On Semiconductor’s brand new chip Akvelon built an application that showcased the new SDK and chip capability in Augmented Reality. Akvelon completed end-to-end implementation, featuring Camera, Camcorder, Burst Capture, HDR, Panoramic Stitch and DVS Assist.
Machine Learning & AI Projects
Meeting Summarizer for Innovate.A.I is a service that helps participants focus on the conversation rather than on taking notes. The organizer of a meeting can include the Meeting Summarizer service into the conversation by either adding a party to the conference by dialing the phone number or by adding the Meeting Summarizer voice-enabled chat bot to the Skype/Slack call.
At the end of the meeting, the service will email the organizer a short summary of the meeting: important action items and notes (approx. 1 screen of bullet points per 30mins of the conversation). A full transcript of the conversation will also be sent as an attachment to the email. The Meeting Summarizer service uses 3rd party speech recognition service (Bing or Google) and a proprietary summarization engine based on the ensemble of models and neural networks. There are a few startups with similar concepts, but none have been released to the public at this time. Read more about the Meeting Summarizer in this blogpost.
Kaggle.com is one of the leading platforms for predictive modelling and analytics competitions. Porto Seguro, one of Brazil’s largest auto and homeowner insurance companies, posted a challenge on Kaggle.com to build a model that predicts the probability that a driver will initiate an auto insurance claim in the next year. A more accurate prediction will allow them to further tailor their prices, and hopefully make auto insurance coverage more accessible to more drivers. A group of two Akvelon machine learning engineers and data scientist enlisted on Kaggle.com competed together and ranked an honorable 22nd out of over 5,000 teams, placing them in the top 0.5% in the competition. Read more about our developer’s solution to the competition here.