Chatbot

Chatbot Development

Oncorre provides a full-cycle Chatbot development service to revolutionize the way you interact with your customers to transform your business. We build enterprise-level AI Chatbots to help you establish a real-time interaction with your customers.

Equipped with Artificial Intelligence, Natural Language Processing (NLP) and Machine Learning technologies, Oncorre creates chatbots that

• Answer Customer Queries
• Conduct Surveys
• Increase Customer Engagement
• Market Your Product
• Monitor Consumer Data
• Send Instant Quotes

Our Services

• Chatbot Architecture

  Our Chatbot experts are equipped to design and develop bots for customers worldwide and implement APIs and plugins tailored to your Chatbot requirements.

• Natural Language Processing(NLP)

  At Oncorre, we apply Artificial Intelligence and Natural Language Processing technology so your customers could simply type or say their queries and the customer service bot will be able to identify their language and provide customer support within moments.

• Chatbot Consulting Service

  We provide consulting services before and after our Chatbot development services have been delivered.If you have any queries, reach out to us and our experts will provide you advice and guidance on Chatbot development.

• Chatbot Deployment

  Once the Chatbot is designed and developed, it’s time for the bot to be deployed and integrated.Our skilled Chatbot developers can do both Cloud or on - premise deployment to maximize digital engagement.

Which Chatbot Approach Is Right for You?

There are different approaches and tools that you can use when building chatbots. Depending on the use case you want to address, some technologies are more appropriate than others. Combining artificial intelligence forms such as natural language processing, machine learning, and semantic understanding may be the best option to achieve the desired results.

• Standard Logic Tree

  These prompt - based chatbots let customers choose from a list of prompts then take them through a series of multiple - choice questions.The application will take them to the most helpful destination based on the answers.This type of chatbot is good for simple queries with a defined scope, as it limits customers to a certain number of inputs.

• Keyword Recognition

  This approach allows customers to submit their written inquiries.The chatbot identifies keywords from the query and directs customers to a corresponding solution.This type of chatbot can be used for a broader range of customer inquiries.

• Machine Learning

  This approach uses a machine learning engine to train itself to deliver an optimal response to a customer query.It learns based on past inquiries and evolves as inputs are analyzed.A large amount of data is needed to train the system, and machine learning of the chatbot application is done in a black box with no insight into what is learned.

• Symbolic NLU

  This approach leverages symbolic AI to provide a more conversational approach to customer service.It uses natural language technology to understand the intent of a customer query.It provides full visibility into the rules that machines use to gain knowledge, with human oversight to adjust the learning models;