- Better, Faster Decisions at Lower Cost
- Business Process Optimization
- New User Experiences
- New Applications
- Deep Insight into Business Metrics
- Quickstart use of new AI platforms
- Machine Learning
- Natural Language Processing
- Predictive Analytics
- Data science skills that make AI useful
Thanks primarily to the economics of cloud computing and big data, AI is no longer a laboratory curiosity. Technologies such as machine learning, predictive analytics, speech recognition and natural language processing (NLP) technologies are in production use today. Likewise, PaaS services oriented to text and speech processing, such as Amazon Alexa and Watson sentiment analysis, are production technologies available create new user experiences and applications. Developers are now armed with a vast array of new tools such as Azure Machine Learning, IBM Watson, Amazon MXNet, Google Cloud Machine Learning Engine, TensorFlow and the various Caffe frameworks. With these solutions, users can move beyond predictive models and begin implementing prescriptive analytics to improve the speed and effectiveness of decisions (made by software) by directly driving decision logic embedded in applications.
NMX is developing applications that utilize several branches of AI, including natural language processing, machine learning and predictive analytics. These applications utilize massive amounts of data and are designed not only to dramatically improve decision-making but also make recommendations and provide analyses that are far beyond the capacity of human beings.
Our data science team focuses on the design and implementation of advanced algorithms that extract insights from complex data. NMX has twenty years experience using large, historical datasets to drive the development of predictive models. We’re experienced in applying a variety of predictive modeling techniques, including regression, decision trees and neural networks. We use a range of third-party tools such as Mathematica, R, MATLAB, SAS, Alteryx and Pentaho, and we have broad experience in data visualization applications that complement analytics.
Based on our experience, organizations should prioritize collecting large amounts of data measuring business factors such as production process outcomes, efficiency, customer satisfaction, behavior of competitors, customers and consumers in a marketplace or social network. If you are not yet collecting such data, NMX can help. Once you have such data available, you can productively apply Artificial Intelligence to your business.
Some Artificial Intelligence applications to consider:
- Know your customer by collecting data in a form that can support further automated processing.
- Listen to your customer by analyzing feedback channels and social networking chatter to measure brand perception and customer satisfaction. Analyze historical patterns in data to find invisible risks and opportunities and increase the accuracy of forecasts.
- Collect engagement pattern metrics to support data-driven channel management and product development.
- Identify suitable metrics and measure inefficiencies in various tactical business operations.
NMX can help you implement these and other options for taking advantage of the new revolution in Artificial Intelligence. We’re doing it today.