Abstract: Techniques for automatically extracting data from documents using multiple deep learning models are provided. According to one set of embodiments, a computer system can receive a document in an electronic format and can segment, using an image segmentation deep learning model, the document into a plurality of segments, where each segment corresponds to a visually discrete portion of the document and is classified as being one of a plurality of types. The computer system can then, for each segment in the plurality of segments, retrieve text in the segment using optical character recognition (OCR) and extract data in the segment from the retrieved text using a named entity recognition (NER) deep learning model, where the retrieving and the extracting are performed in a manner that takes into account the segment's type.

Abstract: Techniques for automatically extracting data from documents using multiple deep learning models are provided. According to one set of embodiments, a computer system can receive a document in an electronic format and can segment, using an image segmentation deep learning model, the document into a plurality of segments, where each segment corresponds to a visually discrete portion of the document and is classified as being one of a plurality of types. The computer system can then, for each segment in the plurality of segments, retrieve text in the segment using optical character recognition (OCR) and extract data in the segment from the retrieved text using a named entity recognition (NER) deep learning model, where the retrieving and the extracting are performed in a manner that takes into account the segment's type.

Abstract: An AI routing framework for a multi-domain chatbot is provided. According to one set of embodiments, a computer system implementing the AI routing framework can receive a user query/request submitted to the multi-domain chatbot, determine an input statement corresponding to the user query/request, and calculate an embedding of the input statement reflecting the input statement's semantic content. The computer system can further identify, from among a plurality of statement embeddings maintained in a repository, a statement embedding that most closely matches the embedding of the input statement, and determine a domain associated with the identified statement embedding in the repository. The computer system can then forward the input statement to a handler of a back-end software system configured to process user queries/requests belonging to the determined domain.

Abstract: Middleware for enabling interoperation between a chatbot application and a plurality of different systems are provided. According to one set of embodiments, a computer system implementing the middleware can receive a request from a user via the chatbot application and automatically determine, based on information included in the request, a system in the plurality of systems that the request is directed to and a service of the system that should be called for handling the request. The computer system can then invoke the service, receive a response from the system, and return the response to the chatbot application for presentation to the user.

Abstract: An AI routing framework for a multi-domain chatbot is provided. According to one set of embodiments, a computer system implementing the AI routing framework can receive a user query/request submitted to the multi-domain chatbot, determine an input statement corresponding to the user query/request, and calculate an embedding of the input statement reflecting the input statement's semantic content. The computer system can further identify, from among a plurality of statement embeddings maintained in a repository, a statement embedding that most closely matches the embedding of the input statement, and determine a domain associated with the identified statement embedding in the repository. The computer system can then forward the input statement to a handler of a back-end software system configured to process user queries/requests belonging to the determined domain.

Abstract: Middleware for enabling interoperation between a chatbot application and a plurality of different systems are provided. According to one set of embodiments, a computer system implementing the middleware can receive a request from a user via the chatbot application and automatically determine, based on information included in the request, a system in the plurality of systems that the request is directed to and a service of the system that should be called for handling the request. The computer system can then invoke the service, receive a response from the system, and return the response to the chatbot application for presentation to the user.