Abstract: A method is disclosed for evaluating network resources on a multi-cloud network platform. A network resource load balancer executes a network resource evaluation application on a server for automatic evaluation of implementing a user application via a first cloud based platform and a second cloud based platform. In response to an evaluation request, automatically and without user intervention, the server identifies a first server located in a first location on the first cloud based platform based on a source identifier; identifies a second server located in a second location on the second cloud based platform based on a target identifier; evaluates performance of the user application on the first server and the second server; in real time, determines performance data including a function latency for implementing the user application; and generates instructions to display the performance data according to a predefined format.

Abstract: Data extraction and automatic validation from digitized documents in non-editable formats is disclosed. Paper documents are digitized or converted into formats suitable for storage on computers or other digital devices. The digitized documents are classified into one of a plurality of document types and based on the document type, document processing rules are selected for analyzing the digitized documents to enable data extraction and automatic validation. The positions and values of the data fields in the digitized documents are obtained using machine learning techniques. The data field values are automatically validated and assigned confidence scores. Data fields with low confidence scores are flagged for manual review.

Abstract: Data extraction and automatic validation from digitized documents in non-editable formats is disclosed. Paper documents are digitized or converted into formats suitable for storage on computers or other digital devices. The digitized documents are classified into one of a plurality of document types and based on the document type, document processing rules are selected for analyzing the digitized documents to enable data extraction and automatic validation. The positions and values of the data fields in the digitized documents are obtained using machine learning techniques. The data field values are automatically validated and assigned confidence scores. Data fields with low confidence scores are flagged for manual review.