Made with machine learning.

BUILT FOR BUSINESS IMPACT.

Infinia ML Contributes to Top Machine Learning Conference
One of the Triangle’s “Best Places to Work”
Infinia ML Named Machine Learning “Hot Vendor”
Infinia ML Wins “Best Machine Learning Company”
Infinia ML Partners with Duke University
Infinia ML Chief Scientist Among Most Prolific Researchers at ICML

PUT MACHINE LEARNING INTO PRACTICE

Our data science team and machine learning technology will help your business:
  • Configure algorithms to lower costs and increase efficiency.
  • Connect results to the real world with a deployment API.
  • Calibrate models after deployment to avoid decay.
Bring your data and let’s get started.

USE CASES

Email Analysis

Processing millions of retail procurement emails to find potential savings. Learn more.

Contract Classification

Increasing the efficiency of legal document analysis. Learn more.

Medical Image Detection

Finding a key nerve network on a mobile ultrasound image in real time. Learn more.

Threat Image Detection

Highlighting potential threats in scanned baggage images. Learn more.

Disease Classification

Predicting infection type (viral, bacterial, fungal) by modeling gene expression levels. Learn more.

Cybersecurity Force Multiplier

Assist human analysts with automated labeling of good and bad data. Learn more.

Stay in the Know

Featured Content
Awards
Our Director of Engineering Wins a Leadership Award
Research Papers
Infinia ML Increases Research Contributions to NeurIPS, the World’s Top Machine Learning Conference
News
Infinia ML Named Machine Learning “Hot Vendor” by HfS Research
Research
VIDEO: Chief Scientist Larry Carin on Convolutional Neural Networks
Enterprises Expect A Two-Year Timeframe For Machine Learning To Go Mainstream A Secure Foundation for Machine Learning Infinia ML Hires Head of Business Development to Accelerate Growth
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Upcoming Book Release 2019

Our upcoming book, Machine Learning in Practice, summarizes the lessons we’ve learned implementing over 100 data intensive projects in the last 10 years. That comes out in early 2019, but you can read chapter excerpts online right now at machinelearninginpractice.com.