CallMiner Research Lab: Our experts talk AI, ML and R&D

The CallMiner Research Lab is a theoretical research team with a wide field of vision. Its research focuses on solutions and approaches that span across artificial intelligence (AI), machine learning (ML), and data science in general.

Technical basics series: PCA for "A/B" testing

Read this post from the CallMiner Research Lab to learn how to perform an "A/B" test and use PCA for ranking feature importance.

Technical basics series: The singular value decomposition (SVD) 101

Singular value decomposition (SVD) is important to data science, as it provides a ranking of features stored by a matrix. The CallMiner Research Lab t...

Five ways to be a better ally in contact centers

Rick Britt, CallMiner's VP of AI, shares his thoughts on diversity in the contact center industry and how people can be better allies to help change t...

Detecting customer emotions with CallMiner

Detecting emotions is hard. It is hard for machines because it is hard for humans. Read this blog to learn why it is so hard and why the CallMiner pla...

Technical basics series: Bayesian inference 101

All statisticians use Bayes’s theorem, even frequentists. What makes you a Bayesian is in how you interpret it. The CallMiner Research Lab breaks it d...

Technical basics series: From Python to Haskell

Haskell is a big functional language. Instead of laying out the language systematically, the CallMiner Research Lab starts with the parts most similar...

Introduction to Responsible AI: The CallMiner Research Lab Responsible AI Framework

CallMiner Research Lab Responsible AI Framework outlines definitions, concerns, as well as driving questions about our tools, models, and datasets.

How much AI is ‘real’ in CallMiner? All of it.

The question should be, “does one company do that better or more powerfully than the competition?” For CallMiner, our solution, with a logical blend o...

Coaching sales interactions takes more than experience – it takes the right technology

Technology continues to evolve. Rick Britt shares why it’s time to start moving the needle using technology like sales conversation analytics.

Introduction to Responsible AI: Unpacking the harms

The latest in our Responsible AI blog series, the CallMiner Research Lab explores two of the main categories of harms that AI outputs can cause: Harms...

We used our own product for Sales Conversation Analytics

The goal of Project Ice Cream was to use our own solution to gain a better understanding of the aspects of business and data that inform our use cases.

Introduction to Responsible AI: Unpacking bias

Part of what makes Responsible AI difficult is the vast set of ideas, theories, and practices that it interacts with. The CallMiner Research Lab unpac...

You’re not really sorry.

The CallMiner Research Lab uses AI to understand and improve conversations between a company and its customers. Here is what the data tells us about s...

Can you legislate AI?

The CallMiner Research Lab weighs in on the proposal recently released by the European Union on how to regulate artificial intelligence.

Technical basics series: A breakdown of Cython basics

Python already has the ability to call external C/C++ code from Python. Cython greatly simplifies that effort and gives your code a performance boost.

Introduction to Responsible AI

Models in today’s world have a real, tangible, and sometimes life-changing impact on the lives of real people, bringing to light an important new side...

What a category is and why it's important

In AI research, we focus a lot of energy on the concept of a category. This blog breaks down what a category is and how we are researching it.

Welcome to the CallMiner Research Lab blog: The cutting edge of innovation

Welcome to the CallMiner Research Lab blog! We are excited to share what we are working on and what we are thinking about.