AI & Machine Learning Implementation

Digital Workforce is a term coined to describe a set of software bots and automated solutions that work alongside human employees to automate repeated processes so humans can focus on value-adding tasks. There are two types of automation technologies. One that automates repetitive handwork, and the other that augments humans by helping in decision-making. We help you identify, prioritize, and align automation use cases to your enterprise strategy. We partner with leading automation software companies and we’re experts in their products. Our deep expertise gives you an edge with your optimization and innovation initiatives.

The challenge most businesses have isn’t a lack of data. The challenge is not only labeling the data to pinpoint outcomes that can be used to train Machine Learning algorithms, but also data integration, data standardization, and feature extraction that power the Machine Learning models. At Productive Edge, our data and Machine Learning engineers are skilled at augmenting your data science team to maximize competitive advantage through machine learning implementation.

The Machine Learning development process has been automated by innovative technologies like DataRobot and H20.ai. Now, data scientists can speed up the time it takes to bring new Machine Learning models to market. What took many months can now take a few weeks. We are experts in Automated Machine Learning (AML) technologies and can help you start up a Center of Excellence focused on the adoption of AML technologies and the rapid delivery of intelligent applications.

A modern data platform with a Customer 360 data hub enables customer analytics and actionable insights. Connecting Machine Learning implementation with these analytics and actionable insights allows the delivery of personalized next best actions. Whether embedded in mobile apps, web experiences, or call centers and customer service, Next Best Actions provide a powerful tool for delivering personalized experiences.

Embedding Machine Learning algorithms within digital experiences is a critical part of enabling intelligent applications. The process of managing the deployment, testing, and then updating these algorithms is critical to ensure desired outcomes are continually achieved. Let Productive Edge help you build your MLOps process and apply the right tools to ensure success.

Edge Computing is a topology where information processing, content collection, and content delivery are placed closer to the sources of the information. The idea is that keeping traffic local and distributed will reduce latency. This includes the Internet of Things (IoT). Empowered Edge looks at how these devices are increasing and forming the foundations for smart spaces, then moves key applications and services closer to the people and devices that utilize them.