There is no blueprint for solving problems that have never been solved before. That's exactly where our data science team excels — and what makes us stand out.

Solving “unsolvable” problems

Work with data scientists who are passionate about machine learning and know how to apply their knowledge to real-world problems. Our data science team consists of machine learning and statistics practitioners who are also seasoned software engineers, ensuring you get clean, tested, and maintainable code. We take the latest research and apply it to real-world problems, bridging the divide between theory and reality.

Predictive Analytics

Turn data into your competitive advantage. We build predictive models that break through the noise and deliver accurate predictions. Using current and historical data, you’ll be able to predict future trends and stay ahead of the curve.

Natural Language Processing and Analysis

Extract meaning from unstructured text with custom language processing and analysis. Using natural language processing (NLP), we can turn your data into insights — whether you want to understand customer feedback better or analyze doctor’s notes on medical records, we can make it happen.

Data Warehousing

Many businesses have a frustrating problem — their most valuable data is siloed in different systems, making it impossible to gather actionable insights. Data warehousing solves this problem by storing data from multiple systems in a centralized environment. With the data stored together in a single location, you can see a complete picture of your business’s health and make data-driven decisions.

Model Design, Validation, and Training

Calculating model accuracy is a critical part of any machine learning project, yet many models are put into production without proper validation. Our data science team can work with your team to validate pre-existing models, design new models, and establish a training program that will produce viable, accurate results using best-in-class tools and the best technologies for the problem at hand.

Data Quality Audit

Clean and complete data is the foundation for any machine learning project. During a data quality audit, our data science team dives into your dataset to analyze whether you have the foundations for a successful data science project.

Business Process Automation

If your business processes require employees to do the same task over and over, you can gain massive efficiencies with machine learning. We can automate most decisions that a human can make in one second. Our team can build systems to automate these tasks, freeing your team up to do more impactful work.

Computer Vision

We build software that can automatically classify image files based on the actual content of the image, such as recognizing products, faces, or other objects in a scene. Using AWS Rekognition and Bayes' Rule, we’ve built robust applications that use facial recognition to identify repeat customers.

Clustering and Network Analysis

We use data analysis to uncover structure in your data. By grouping similar entities together, you can profile the attributes of different groups. Get insights into underlying patterns of different groups and how they fit into the larger system.

A Facial Recognition-Powered Beer Kiosk System

We worked with Hop to develop the world’s first self-serve beer kiosk to be powered by facial recognition technology.

Read the Case Study

Meet the Practice Lead

As a Senior Data Scientist and Data Science Practice Lead at Very, Michael Simpson collaborates with clients and other team members to solve difficult problems. Michael has leveraged machine learning to examine social communication networks, detect fake news, analyze legal documents, and used facial recognition to authenticate users.

"Very’s data scientists came up with suggestions that were in the back of my head but I thought, ‘that’s probably not possible.’ And they made it happen."
- Anthony Connelly, founder of Hop

Machine Learning Consulting Services

Real data scientists, unreal results