You take communication seriously. So why should your customer conversations be anything but exceptional?

Use Cases

Wireless Connection

Your customers can now contact for all their questions regarding their wireless connection, their subscription, their account, technical troubleshooting, etc.

Cable & Streaming can take over all customer care conversations related to your streaming offerings. Automate service questions, account information, network coverage, issues, plan details.

Billing, Collections & Accounts Receivable

Let take the load off of your billing and collections department. Automate more conversations, with the same amount of agents, to bring in more revenue. can also manage credit risk and detect fraud.

Example demonstration of hypothetical use case

“I watched [Kylie] automate our most complex chats in 1.5 minutes. These are very complex chats that require human decision making.”

— Director of Credit Risk, 3rd Largest US Telecom Company


To Build a Smarter Chatbot, First Teach It a Second Language

This blog post was originally posted on MIT Technology Review by Will Knight From Alexa and Siri to countless chatbots and automated customer support lines, computers are gradually learning to talk. The only trouble is they are still very easily confused. A research team at Salesforce has come up with a clever way to improve the performance of many modern language programs—teaching an algorithm to speak another language before training it to do other tasks.

Posted by Shayaan Abdullah on 10/4/17

Topics: Artificial Intelligence, Machine Learning, Sentiment Analysis

Formulating an A.I. Strategy

Evaluating artificial intelligence in the enterprise can seem like a daunting task. The team has worked with several leading organizations and has learned key insights in how to approach evaluating A.I. The following points can provide guidance and best practices in how to formulate an A.I. strategy.

Posted by (Josh Adragna) on 10/2/17

Topics: Artificial Intelligence

The Beginner’s Guide to Text Vectorization

This blog post was originally posted on MonkeyLearn by Rodrigo Stecanella Since the beginning of the brief history of Natural Language Processing (NLP), there has been the need to transform text into something a machine can understand. That is, transforming text into a meaningful vector (or array) of numbers. The de-facto standard way of doing this in the pre-deep learning era was to use a bag of words approach.

Posted by Divya Susarla on 9/27/17

Topics: Machine Learning, natural language processing, text vectorization

Security Certificates


Go Live in
90 Days. leads the industry in deployment time. We understand that every moment wasted equals lost opportunity. With, get fully ramped up in less than 90 days.