Multilingual Chatbot Platform

#Data analytics
#Data science
#Machine learning
#NLP

Business Challenge

Chatbots are a perfect fit for global businesses that used to spend enormous sums of money on customer support. These bots are especially relevant for companies that want to organize their users into a community and keep them loyal to their brand. Answering repetitive questions in rare languages is another challenge chatbots can solve.

Understanding the value of chatbots enticed our client to create a platform that lets businesses build multilingual chatbots powered by a natural language processing (NLP) engine.

Solution Overview

The platform Quantum developed allowed generating a chatbot, integrating it into a website or other infrastructure and setting up the chatbot flow logic. These conversational assistants help the support staff cooperate with customers.

Our team built an AI-powered chatbot with features like:

– text-to-speech recognition

– speech-to-text recognition

– multilingual approach

– mixed-language understanding

– easy system integration

Project Description

Having taken into account the business challenges of this project, Quantum decided to use Google BERT as the core for an NLP model. This model can understand and answer questions in multiple languages on various subjects from the box, decreasing the implementation cost dramatically.

Quantum data science engineers used Google BERT to train the model architecture on one language modeling objective and then fine-tune it for a supervised downstream task.

As a result, the model recognized specific terms and subjects and generated SQL-similar requests to databases to get the requested data (like financial information, information about new products, etc.).

To automate support services, the Quantum team:

– reworked the front-end and back-end

– completely redeveloped bot flow storing and versioning

– enhanced various serviced for human-agent interaction, human-bot interaction and multilingual support

The Agile methodology allowed us to assess the project’s direction during the development cycle while keeping the focus on the business value.

The solution has the following features:

Multiple language support.
Unlimited agents & teams. Users can organize agents and aliases into teams to handle the most complex customer support cases.
Agent performance.
Agent and automation performance analysis. Shows information about savings and improvements.
Proactive chat. The client’s customers can engage their target audience with website and integration triggers.

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Technological Details

The Quantum team used NLP to create a question answering system enhanced with machine learning that cooperated with input questions and provided answers to them.

NLP helps the system identify and understand the meaning of sentences with proper context.

Quantum chose Google BERT because it is trained on enormous volumes of data, and it makes the process of language modeling easier. The main benefit of using a pre-trained model of BERT is substantial accuracy improvements compared to training on these datasets from scratch.