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ScienceSoft assisted a US nationwide telecom leader with Hadoop configuration, helping remove a single point of failure and ensure uninterrupted access to critical telecom data for its 400+ clients.
Having 10-year fruitful cooperation with ScienceSoft, the Client turned to our developers for help in creating new features for its LMS product.
In just three weeks, ScienceSoft audited the accounting module of a web-based home healthcare delivery app. Our expert team detected multiple flaws in the accounting logic and provided actionable recommendations on how to address them.
ScienceSoft handled the development of the SaaS platform for labor market analytics. The solution works quickly and reliably with a large amount of data and presents easy-to-digest results to users.
ScienceSoft implemented a self-service customer portal for a Saudi Arabia’s leading logistics provider, and helped the company streamline cargo storage and pickup booking services across several airports.
ScienceSoft audited the existing mockups, elicited the requirements for the system’s interface, and assisted in delivering a seamless UI. We created a set of widgets displaying real-time and historical data transmitted by traffic lights controllers.
ScienceSoft helped a US research university standardize millions of research data entries across 40,000 parameters. We delivered a Power BI solution that allowed the Client to cut time spent on data search, explore data at different angles, and automate reporting.
ScienceSoft created a solution that helps a US investment firm screen financial market websites and flag news updates based on user-defined criteria, like a target company and a search period. The Client can now spot events that can influence investment decisions.
ScienceSoft conducted a comprehensive UX audit and redesigned the UX/UI of a Xamarin mobile app to help a US fitness startup drive higher user engagement. Our team also developed new features to increase app value for fitness pros and enthusiasts.
ScienceSoft empowered a leading oil drilling equipment manufacturer with an application for detecting drill bit defects and performing drill bit wear analysis. The solution is based on machine learning and visual recognition algorithms.
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