Data Science, Artificial Intelligence & Machine Learning
Improve your organization’s efficiency and customer experience with world-class machine learning and artificial intelligence.
Point of View
Beat the odds and actually create value with artificial intelligence and machine learning.
Artificial intelligence (AI) is a strategic priority on more than 80% of companies’ corporate roadmaps, yet over 80% of all AI projects will never make it past the proof of concept stage. Most organizations will fail to scale their own AI and machine learning (ML) models. Other organizations leverage outsourced AI and ML capabilities and are stuck with a black box solution they have no control over and no understanding of how it predicts and recommends.
We equip clients with advanced capabilities within data science, ML, and AI at enterprise scale to better target customers, improve customer experience, optimize inefficiencies, and ultimately lead the market. Let’s work together to accelerate your data science capabilities using established tools and approaches combined with our expertise and curiosity to give your organization AI and ML platforms you can control and understand.
Capabilities
Don't just talk about AI and ML, take the market with new data science capabilities.
We believe in creating solutions that are sustainable for your organization. Use established tools and approaches combined with our expertise and curiosity to create success.
Data Quality Assessment
Understand your data maturity by utilizing our automated profiling techniques that will gauge the current state of your data and allow for new data to be monitored.
Customer Targeting
Utilize segmentation and reinforcement learning techniques to better understand your customers and optimize behaviors such as click-throughs, up-sells, reactivation, and retention rates.
Process Automation
Allow employees to focus on more important and engaging tasks by automating select processes through chatbots, robotic process automation (RPA), and machine learning models.
Document Typing
Classify digitized and non-digitized documents using advanced natural language processing (NLP) techniques such as optical character recognition (OCR) and sentiment analysis.
Image Classification
Tag existing and/or incoming image files through computer vision tools and deep learning models.
Anomaly Detection
Automatically detect outliers within your data using ensemble machine learning models that can continually learn and adapt to new data.
Case Studies
