Few things about Chatbots

-
" A chatbot is a computer program or an artificial intelligence which conducts a conversation via auditory or textual methods. Such programs are often designed to convincingly simulate how a human would behave as a conversational partner, thereby passing the Turing test."
According to numerous researches, chatbots can bring 90% of accuracy in solving user problems without human interactions. Everyone pretty much at this point have used one of this Omnipresent in some form. Omnipresent is nothing but Artificial Intelligence-based Chatbots. These are some well-known Companies who offer solutions like Siri, Alexa, Cortana, Watson, etc..









Key benefits of using chatbots:












Types of chatbots:
  1. Informational Bots
  2. Application Bots
  3. Productivity Bots
Some of the usecases:
  • Call Center
  • Customer/Help-Desk Service
  • Marketing
  • Sales
  • Workflow
Conversational Partners/Interfaces are what serves the purpose of customer experience in a different way. Main Conversational Interfaces:

Voice-based Conversational Interfaces: There are plenty of devices are coming into this space every day. Siri in Apple Devices, Alexa devices, Cortana from Microsoft devices are few examples.

Chat-based Conversational Interfaces: Conversational Interfaces are becoming most favorite to promote brand and awareness. Also, Registration for events or booking flights, hotel rooms, and cars are very favorite use case these data for Chat based Conversational Interfaces.

Best chatbot development tools available for the developers to build production-ready chatbots.
  1. Botkit is one of the leading open source chatbot development frameworks.Botkit supports major messaging channels such as Facebook, Slack, Microsoft Teams, SMS etc. One of the important features of Botkit is supporting middlewares (or plugins). Middlewares can add to the core bot running processes and make changes both incoming and outgoing messages.
  2. Botpress is another leading open-source platform for building and managing chatbots. The best part of Botpress is it provides UI where developers and non-technical people can manage the chatbots after the deployment. Botpress has many nice features such as The Flow Builder and Dialog Manager. Flow Builder and Dialog Manager make it easier for developers to build and debug complex conversation flows. 
  3. Rasa is an open source chatbot development frameworks. It has two major components Rasa NLU and Rasa Core. Rasa NLU is responsible for natural language understanding. Rasa core is a framework for building conversational chatbot. Rasa core allows more sophisticated dialogue, trained using interactive and supervised machine learning.The major advantage of using Rasa Stack should be the chatbot can be deployed on your own server by keeping all the components in-house. It is possible to use Rasa Core or Rasa NLU separately. Rasa is production ready and used in large companies everywhere.
Resources:
  1. www.google.com
  2. https://en.wikipedia.org/wiki/Chatbot
  3. https://botkit.ai/
  4. https://botpress.io/
  5. https://rasa.com/

Popular posts from this blog

Connecting Claude to Pega Infinity 25.1.3 via MCP — Step-by-Step

-
Image
Enable AI-powered access to your Pega Investigative Case Management data directly from Claude prompts using the Model Context Protocol (MCP) and OAuth 2.0. What is MCP and why connect Pega to Claude? The Model Context Protocol (MCP) is an open standard that lets AI assistants like Claude securely call tools and read data from external systems — all from a natural-language prompt. Think of it as a universal adapter between your enterprise systems and AI. Pega Infinity V25.1.3 ships with a first-class MCP service built on its existing REST framework. Once enabled, Claude can: Query and summarize investigative cases without switching apps Retrieve assignment details and case status on demand Trigger Pega workflows from conversational prompts Version requirement: This guide is based on Pega Infinity V25.1.3 (Community Edition) with the Rule-Service-MCP rule type. Earlier versions may not include native MCP support. Architecture overview The connection uses three layers: Claude as the AI c...
Read more

itextpdf API to generate PDF doc from an image file using Pega PE

-
Image
Probably some of the techies might have an idea on an opensource called " itextpdf " (earlier name is lowagie ) to convert an image file(png,jpeg,jpg,tiff,gif etc.) to a PDF file. It is very simple to use this API in Pega function to build the logic using java code. Moreover, this API comes in one single jar file and we need to import it in Pega before we start using it.  I see the conversion comes good in PDF file but not sure if any limitations of this API in terms of conversion is like formatting, font, images etc. So far so good and may be we can keep this API as one of our solutions while working on the requirements accordingly.  Heard that same API can be used to convert the text file to PDF but I didn't explore on it. Those who are interested to work on text -> PDF can take a look at the documentation. Don't hesitate to contact me offline for any further discussion in this context :) :) Prerequisites for doing this exercise: 1) itextpdf 5.4.0 jar file 2) Peg...
Read more

Understanding of Hugging Face platform for AI/ML platform

-
Image
Hugging Face is a platform that provides tools and libraries for natural language processing (NLP), machine learning, and artificial intelligence. It is known for its Transformers   library, which offers pre-trained models for tasks such as text classification, translation, question answering, and more. Hugging Face also hosts a model hub where users can share and discover pre-trained models. Hugging Face is useful in various domains, including: Natural language processing (NLP): Provides tools and pre-trained models for tasks like text classification, translation, sentiment analysis, and question answering. Machine learning research: Offers state-of-the-art models and datasets for researchers to experiment and innovate. Data science and analytics: Helps data scientists analyze and interpret large volumes of text data. AI application development: Enables developers to build AI-powered applications with ease using pre-trained models and APIs. A very simple exercise using the google...
Read more