Everything you need for an outstanding customer support
Articbot is based on ASCORE (Articbot Semantic Core engine) developed by us. It is a composition of various techniques such as natural language processing, machine learning, AI etc. It allows exploring the content in user’s context deeper than traditional text matching. Ascore is written in c# language. Ascore is a bot framework for articbot. written in c#.
Company can set the information about their product/service as a question and answer format. Articbot will learn from these questions and answers.
Chatbots built with Articbot can be easily deployed to multiple communication channels with a simple configuration.
If you’re using a support ticketing system like Freshdesk, Zendesk etc, can easily integrate with Articbot.
Our bot framework (ascore) trying to find out the maximum possible way to find out the intent and entity from user context and map with this to company’s predefined data.
Banking and finance sector can setup the EMI calculator for their customers. Users can get EMI calculator by using query request.
The world is unique but it speaks multiple languages, to answer your global customers we support 100+ languages.
After creating the support ticket, now you can check your ticket status by using chat.
We are the only one who providing the 24x7 customer support without any human agent.
By default Articbot ask email id to the user and the user query and email is sent to the company. When the company update the solution, bot will send the solution to the user.
Articbot has the potential to analyze the user context based on the situation.
Articbot can make decision for Closed-ended questions from user context.
Articbot can think out of the box by using the deep analyzing the user context. Machine learns how to act in a certain environment.
Knowledge about Payment methods
Knowledge about languages
Knowledge about locations
Knowledge about documents
Knowledge about professions and technologies
Knowledge about common customer issues
Articbot can handle complex user context. Our entity extraction process is effective for processing complex queries.
In each chat our algorithm tries to understand emotional variations of the customers to answer them
Articbot can identify the person info from the user context. It can fetch person name, email, mobile, designation, place, qualification, etc.