Retail

Conversational AI to power your consumers. Train Kylie to understand your products deeply and deliver consistently exceptional service.


Use Cases

Retail

Take care of your customers with no human involvement. Kylie can automate conversations regarding returns, exchanges, order information, order tracking, product questions, promotion rules, etc.

Billing & Account Information

Automate any conversations related to account information, billing method, payment processing, refunds, etc.

Example demonstration of hypothetical use case


Resources

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 Kylie.ai 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@kylie.ai (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


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