Smart Chatbot Using BERT & Dialogflow - https://demos.pragnakalp.com/bert-chatbot-demo-large-text

Smart Chatbot Using BERT & Dialogflow(Beta)

Try your hands on our most advanced fully Machine Learning based chatbot developed using BERT and Dialogflow. In this closed-domain chatbot you can ask question from the book "India Under British Rule". Now our BERT based system fetches answer within 3-4 seconds (without GPU) from the text of half a million characters length.

GPT2 Text Generation Demo - www.demos.pragnakalp.com/gpt2-text-generation

GPT2 Text Generation

Machines are capable of writing content now! Using GPT2 we have created a text generation system which writes on the given input. Just provide your input and it will complete the article. Also, you can check thousands of articles created by Machine on our website: MachineWrites.com - Fully AI based GPT2 Generated Articles Demo

Sentiment Analysis - www.demos.pragnakalp.com/bert-sentiment-analysis

Sentiment Analysis

Using various methods and algorithms we have developed multiple Sentiment Analysis demos. Try them out!

BERT based chatbot - https://demos.pragnakalp.com/bert-chatbot-demo?language=english

Closed-Domain Chatbot using BERT

Unlike our BERT based QnA system, you can get quicker responses for your queries. It looks like a proper chatbot with a caveat that it is closed-domain which means it fetches answers from given paragraph only. It is available for multiple languages.

BERT based QnA - https://www.pragnakalp.com/demos/BERT-NLP-QnA-Demo/

BERT based QnA

Question and Answering system from given paragraph is a very basic capability of machines in field of Natural Language Processing. Test our BERT based QnA with your own paragraphs and your own set of questions. Not only for English it is available for 7 other languages.

Named Entity Recognition Demo

BERT and BIOBERT Based Named Entity Recognition (NER)

Our demo of Named Entity Recognition (NER) using BERT extracts information like person name, location, organization, date-time, number, facility, etc. from the given input. And our demo of Named Entity Recognition (NER) using BIOBERT extracts information like Anatomy, Disease, Protein etc. from the given input. Try with your own input and provide your feedback.