Very often, companies are faced with fragmented, obsolete processes, bottlenecks and obstacles that erode profits, lower product quality and increase failure risk. We help our clients by implementing a structured approach that consists of the following steps: First, define the challenges and identify their causes. Second, prioritize targets based on value and feasibility given the data at hand. Third, apply data analytics and computational models, in an iterative manner and in conjunction with the business. The algorithmic methods that we use to solve these problems include mathematical optimization, machine learning, graph theory and multi-scale modeling and simulation on HPC systems.
Past projects include:
It is often said that Data is one of the largest assets that a company has, a treasure drove awaiting to be found. In reality, data are not worth the hard drive they occupy if they are not collected, processed and analyzed properly. Even so, outcomes must be disseminated and understood by the business, have value to it and hopefully lead to clear actions. Together with our partners, we have developed advanced analytics to perform these tasks and transform amorphous datasets to actionable insights. The methods we utilize are the latest in supervised and unsupervised machine learning, anomaly detection, reinforcement and transfer learning. We also partner with Natural Language Processing (NLP) and Computer Vision experts whenever we need additional expertise to deliver a project. We work together with statistics experts to ensure that our solutions will stand the test of time in an uncertain world where everything is on flux.
Past projects include the analysis of financial data from a corporate client to predict sales and forcast product availability, creating predictors for disease onset and learning the customer satisfaction from chats and communication data.
Creating an Artificial Intelligence is more than just putting data analytics and stunning visualizations together. It needs a system that can continuously process information, monitor events and act upon them. Automated ways to analyze and learn from past experiences to fine tune actions is another key feature. Last but not least, communication with the user in a clear, intuitive way is essential.
Projects include an autonomous AI for a large conglomerate that would like to create a curated knowledgebase based on past experience, a monitoring system for highway maintenance and a clinical decision support system based on best practices.
Whether it is a desktop application or a smartphone app, our software engineers provide client-focused solutions to house the data analytics solutions of any project. Our teams work based on agile methodologies in a variety of languages and platforms so we can better match the business and functional specifications of your business need.
Projects here include the software engineering layer of the various data analytics projects that we have undertaken, including a mobile app for a client in the transportation business, a clinical decision support application for physicians, a database management and machine learning web service for several manufacturing processes.