zCon Chatbot Framework Accelerates Your Customer Support

Chatbots are a boon to customer service-driven businesses. At zCon we have developed a framework that can help you easily deploy and run a chatbot. Compared to the 100% time required to create a business specific-chatbot, our framework can do it for you with 60% less time and effort.

What is a Chatbot?

A chatbot is a conversational agent or software applications that mimics written or spoken human speech for the purposes of simulating a conversation with a real person. Chatbots are most commonly used for customer service.

They are available to users for web-based applications and standalone applications.

How Do Chatbots Work?

At the centre of chatbot technology lies natural language processing or NLP, the same technology that is used by virtual assistants such as Google assistant, Apple’s Siri, and Microsoft’s Cortana.

Whenever text is sent to chatbot:

  1. It parses / processes the text sent by the user.
  2. Passes processed text to algorithms that interpret and identify what the user said, means and wants.
  3. Sends response to user based on what user wants.

Advantages of Using Chatbots

  • Chatbots can be used through different channels like SMS, live chat, social media or email.
  • 24 X 7 availability.
  • Chatbots help to collect data and we can analyze collected data.
  • Responses by chatbots are consistent every time.
  • Cost effectiveness.
  • Chatbots can respond to customers immediately.
  • Is the best way to communicate with businesses.

Chatbot Development Framework

A chatbot development framework helps build, connect, publish, and manage chatbots. It uses one or more machine learning algorithms and allows users to connect to various platforms like Google Assistant, Amazon Alexa, Mobile apps, Messenger, websites, Slack, Twitter, and more.


Conversation  Conversation is interactive communication between two parties where information is exchanged between two parties. 
Intent  When the user asks a question, the agent will try to match corresponding intent. To understand the question better by intent, we need to feed as much as training data as we can.  
Training phrases or utterances  These are example phrases for what end-users might say.  
Parameters  When an intent is matched at runtime, the chatbot framework provides the extracted values from the end-user expression as parameters.  
Responses  Text, speech, or visual responses to return to the end-user.  
Entity  The agent needs to know what information is useful for answering the user’s request and that data is called entities. Defines the type of information we want to extract from user input.  
Context  Contexts are similar to natural language context. Context helps the agent to talk more like a human by maintaining the context and replying in the context to end users.  
Integration  Chatbot framework provides integration with one or more popular conversation platforms.  
– Telephony and IVR integrations
– Built-in integrations
– Open source integration
– Independent integrations  


zCon Chatbot Framework

zCon has developed a chatbot framework with the help of which you can create a chatbot specific to your business specific chatbot in a cost effective and faster way. We have a number of satisfied clients who have used our chatbot framework to create their business specific chatbots.

zCon chatbot framework allows defining two types of workflow:

  • Static workflow
    • Workflow definition contains simple questions and the static response for questions.
      • Example: “What is your customer care phone number?”
  • Dynamic workflow
    • Workflow definition can get data from their (customer’s) specific API and form a response to provide to end-users.
    • Workflow definition can contain one or more conditional decision to provide different response to end-user.
      • Example: “Last order detail”.
      • Example: “Book a Premium flight ticket on ABC Flight on 12 May”, where response could be:
        • “No more seats available on ABC Flight for premium class” or
        • “Flight ticket is booked. We have sent you flight ticket details over email and SMS”.

Technology We Used

  • Dialogflow
    • Chatbot is created build and published using Dialogflow chatbot framework.
  • .Net Core
    • NET Core is a free and open-source, managed computer software framework for Windows, Linux, and macOS operating systems.
  • SQL Server
    • SQL Server database is used to store the conversation detail and chatbot configuration.
  • Botium
    • Botium is for testing chatbot. Botium is a suite of open source software components that support chatbot makers in training and quality assurance:
      • Chatbot makers define what the chatbot is supposed to do.
      • Botium ensures that the chatbot does what it is supposed to do.

zCon Framework Components

Conversation Designer (In progress)

Conversation Designer is a visual designer tool to allow businesses to define the conversation or workflow for business specific custom chatbot.


Configurator takes the conversation definitions defined by businesses and creates or updates the chatbot with definition.


Webhook is fulfillment to provide the response required by end-user when they start conversation with Dialogflow agent. With the help of a webhook, a chatbot can integrate with business specific API to obtain the specific data for the end-user.


Databases stores configuration and definition of each and every workflow/conversation. It stores the conversation logs for each end user conversation. So that the data can be analyzed by businesses and it can provide better service to the end – user after better training.


zCon chatbot framework is flexible enough to support integration with multiple platforms. Current integrations supported by  chatbot framework are:

    • Google Assistant
    • Google Home
    • Facebook
    • Email
    • SMS
    • Botium
    • Twilio

Why use the zCon Chatbot Framework?

    • Leaves the technical chatbot complexity to framework.
    • Minimize the efforts required to create and publish chatbot for business.
    • Minimizes the cost.
    • Has quick and easy integration with business specific API.
    • Offers cross-device support.
    • Delivers natural and rich conversational experiences.
    • Works with an array of platforms.
    • Helps to evaluate chatbot’s performance with analytics tool.

AI Chatbot Development Frameworks

Some of the well-known chatbot development frameworks are:

  • Microsoft Bot Framework
  • Dialogflow
  • IBM Watson
  • Amazon Lex