Data transformation caching in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: identifying, in dependence upon one or more machine learning models to be executed on the GPU servers, one or more transformations to apply to a dataset; generating, in dependence upon the one or more transformations, a transformed dataset; storing, within one or more of the storage systems, the transformed dataset; receiving a plurality of requests to transmit the transformed dataset to one or more of the GPU servers; and responsive to each request, transmitting, from the one or more storage systems to the one or more GPU servers without re-performing the one or more transformations on the dataset, the transformed dataset.

Methods are provided for semantic processing of data files including detecting formats of data embedded in the data files and converting the data to formats compatible with a data analysis tool. The method may comprise determining if the data file comprises signature characteristics associated with a known data format and, if so, determining a set of data manipulation operations associated with the known data format to convert the data file to a compatible format for the data analysis tool. The method may further comprise semantically analyzing components of the data files to assess formatting across a required set of criterions needed by the data analysis tool and determining sets of data manipulation operations to perform to convert the data file to a compatible format.

The disclosed systems and methods may receive a data record from either a legacy data source or a modern data source and determine whether the record satisfies a first set of validation rules. When the record fails to satisfy the first set of rules, reject the record for storage in a data store. When the record satisfies the first set of rules, determine whether the record satisfies a second set of validation rules. When the record satisfies the second set of rules, store the record in the data store with an indicator that the record satisfies the all rules. When the record fails to satisfy the second set of rules, if the source was a modern data source reject the record, and if the source was a legacy data source store the record in the data store with an indicator that it fails to satisfy the second set of rules.

An information processing apparatus includes a processor configured to: in compatible change of a first document to a second document in a second format, the first document being generated in a first format, the second format being different from the first format, when the first document contains incompatible data which is not compatible with the second format, convert the incompatible data to data compatible with the second format, and add the converted incompatible data to the second document; and embed link information for the converted incompatible data at a position, in the second document, corresponding to an original position, in the first document, of the incompatible data.

A system including a database configured to store data characterizing a plurality of emails, a plurality of projects, a plurality of vendors, and a plurality of invoices. Each invoice of the plurality of invoices includes data characterizing a project of the plurality of projects, a vendor of the plurality of vendors, and a plurality of invoice data. The system also includes a computing system communicatively coupled to the database and including at least one processor. The at least one processor is configured to receive a file in a first format, convert the file into a second format, determine a first project, a first vendor, and a first plurality of invoice data based on data in the file, prepare a new invoice based on the first project, the first vendor, and the first plurality of invoice data determined, and provide the new invoice in a third format.

Universal, automatic file conversion may be provided by a universal file conversion system or application. An input file may be received by the universal file conversion system. An input file type for the input file and a recipient of the input file may be determined. Programs available to the recipient for accessing a file may be determined. A target file type accessible to the recipient may be determined for converting the input file. A sequence of file conversions to convert the input file to the target file type may be determined. The input file may be converted to the target file type based on the sequence of file conversions. The converted file may be provided to the recipient. The recipient may return the converted file, and the converted file may be automatically converted back to the original input file type and provided to the original source of the input file.

The invention relates to computer-implemented systems and methods for analyzing and standardizing various types of input data such as structured data, semi-structured data, unstructured data, and images and voice. Embodiments of the systems and the methods further provide for generating responses to specific questions based on the standardized input data.

One embodiment is an information management system which is capable of routing and/or delivering the information to a user. The system can include a notification system for providing a notification to the user associated with the information.

Systems and methods for improved data conversion and distribution are provided. A data subscription unit is configured to receive data and information from a plurality of data source devices. The data subscription unit is in communication with a virtual machine that includes backtesting utility configured to generate backtesting data using one or more statistical models and one or more non-statistical models. The backtesting utility may translate the backtesting results into one or more interactive visuals, and generate a graphical user interface (GUI) for displaying the backtesting results and the one or more interactive visuals on a user device. The backtesting utility may update one or more of the displayed backtesting results and the one or more interactive visuals without re-running the modeling steps.

Documents, such as those that may or will be the subject of a litigation, may be managed by automatically determining that a document, such as an email or other communication, is privileged or producible such that superfluous documents may be removed to improve data storage and reduce the burden on storage, processing, and communication resources. Additionally, documents such as emails may comprise attached or embedded documents (e.g., attachments) which may be similarly or independently classified from their associated email. After determining privilege, such as via metadata associated with a sender/receiver of an email, similarly categorized documents may be grouped for presentation and/or storage. The documents may be indexed, such as by entries within a production log, to further facilitate accurate production and management of non-privileged documents, as well as, the exclusion of privileged documents. Documents not required for production may be indexed and/or purged from storage.