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June 26

Open Plaza Talk

QBox: How To Improve Your Training Data

In this short talk, Benoit Alvarez will take you through ways to train and test multiple NLP technologies. With this step-by-step approach, you’ll start to understand how to fix common issues, and what types of solutions a specific provider responds well to.


Benoit Alvarez

Benoit Alvarez

Chief Technology Officer

Benoit started his career working for the International Radio Astronomy Centre in France, building software with scientists who were studying Saturn. He then joined Thales Armament, working on on-board software for missile guidance systems. After 15 years of conceptualizing and building enterprise solutions, Benoit retrained in AI (studying under Professor Andrew Ng) and successfully achieved AI certifications from Stanford University and Coursera. As Volume moved toward AI-powered conversational platforms, Benoit conceptualized two key products: Volume’s advanced AI-powered conversational platform and QBox. The latter was the first of its kind and is a patent-pending technologies tool, recognized by Gartner as a chatbot corpus-management and training tool.

Volume AI



Volume AI

Copy of BRN19 Logos for company page- 45 is lowering the barriers to entry and adoption for organizations looking to invest and leverage myriad business and operational benefits of conversational platforms, such as chatbots. As a recognized leader in Conversational AI and Natural Language Processing (NLP), Volume is in a unique position with two subscription-based products already in-market. Volume also has a capability set that is unrivaled in its field of AI right now. The first product is ‘Big Brain Chatbot’, a pre-built conversational platform that is independent of any NLP engine. Big Brain Chatbot plugs into a customer’s NLP engine or engines of preference, be that AWS Lex, Facebook’s, Dialogflow from Google, IBM Watson Assistant, Microsoft LUIS or Rasa NLU. Big Brain Chatbot has integrated capabilities such as speech recognition, long/short-term memory, sentiment analysis and human-in-the-loop. Volume’s second product, QBox, is a first-to-market SaaS solution that helps companies already utilizing NLP-based chatbots to better understand the quality of their training data to improve overall performance and to scale with a high degree of confidence and accuracy. QBox visualizes the impact of a change or addition to the NLP Data Model training data, down to a single intent. QBox allows chatbot developers, managers and/or administrators to run tests after training to identify areas of regression and to retrain where performance has shown to have been negatively impacted. QBox supports NLP Data Models built with Dialogflow, IBM Watson Assistant, Lex, LUIS, Rasa and Volume also develops bespoke solutions for customers looking at specific use cases for voice-first solutions and works with multiple customers in many industry sectors, namely Banking, Financial Services, IT, Retail, Automotive and Professional Services. Volume’s products are being used by organizations such as Accenture, American Red Cross, Banco De Galicia, Castrol, Finastra, NetApp and Sky.

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