Chatbot

We provide AI assistants to help growing business demands and customers’ needs by retaining important context and holding back-and-forth conversations using machine learning-based dialogue management.

What is a Chatbot?

A Chatbot is a service, leveraging artificial intelligence technologies, that you interact with via a chat interface. While a Chatbot can be functional and solve business problems without the need for human intervention, it can also engage and retain site visitors. An engaged site visitor is more likely to convert into any purchasing activity. Chatbots can be programmed to carry out automated actions.

How do Chatbots Work?

Chatbots understand your messages through a Natural Language Processing (NLP) engine, such as Microsoft Cognitive Services or IBM Watson. The point of NLP is not to interpret sentences word-for-word but to extract the ‘intent’ behind the messages. For example, the intent of the question “how will be weather tomorrow?” could be “weather forecast.”

What’s Behind a Chatbot?

Chatbots are all about answering questions. Chatbots make the whole experiences of getting answers by asking a series of questions fun, interactive and time-saving. But what goes on behind the scenes? What multitude of technologies, the outcome of decades of research & development efforts, come together seamlessly to work behind the scenes to get your answers?

Where are Chatbots Used?

E-commerce Chatbots

enable buying of goods and services.

Content Chatbots

share relevant content with you. news or weather.

Banking & trading

provide financial services.

Workflow Chatbots

Automate business workflows.

IoT Chatbots connect

Us to our smart homes, cars, and devices.

Personal Assistant

Personal communications & task management.

Chatbot Framework

This chatbot has been developed using state of the art natural language processing (NLP) and machine learning models, with a strong grip on dialogue flow, which enables the bot to hold contextual conversations with users. Another key factor is to get enough control over the bot, unlike many frameworks. The distinguishing feature of our framework is that it understands the user intent so well, learns from it and also responds to it intelligently when required. The problem with other frameworks is that we cannot run them in our environment and the data has to be sent to the third party as most of the tools are cloud-based. This is the last thing that a client wants. So our framework gives us full liberty in this case. It can be built and deployed in our environment without the interruption of a third party.

Before discussing the major components of this framework, one needs to get the idea of the following terms:

Intent

Intent is a thing that a user wants or aims at.

Entity

Entity is the structured data that is to be extracted from user input.

Stories

Stories is the interaction between a user and bot in the form of intent and then the action of bot in response to it.

Actions

Action is the response of bot to user input. It can either be asking for more details or answering questions. Our chatbot framework consists of two main components:

Natural Language Understanding Component

It is a natural language understanding library which helps bot understand what the user is saying. Firstly intents and some variations of questions that can be asked by a user have been defined then we trained the NLU model with input and extract structured data/entities. NLU in our chatbot framework benefits in many ways. For example, we don’t have to send our data to any third party and we can tweak and customize models for our training data. So this NLU component makes our framework unique and intelligent.

Core AI-Machine Learning Component

Our core AI-machine learning component comes with machine learning-based dialogue management. The purpose of the core component is to take the structured data from the NLU component as input and use it to predict the best response/action to that using a probabilistic model like Long short-term memory (LSTM) neural network.

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