METHODS AND SYSTEMS FOR CONVERTING DIGITAL DATA AND DOCUMENTS INTO SINGLE VERSION DIGITAL DOCUMENTS WITH CONTENT MANAGEMENT.

Abstract

This application pertains to the apparatus and methods for converting pre-existing data and documents and creating new documents into "Single Version" digital documents with content management to eliminate document content integrity issues and concerns, while providing users with 100% document integrity. In some examples of pre-existing data and documents, users can import all document format types and all document file types. The system is configured to read the document, convert it to digital format, understand and contextualize key terms, key parts, key dates, signatures (or missing signatures) within the document, and provide a series of intelligent advisor recommendations through CIPBITS.The system encrypts data and documents while creating and assigning an embedded digital serial number as a unique identifier. This ensures that it is the only valid version of the document once all parties have signed and the sender has sent the data and documents to the intended recipient(s) for review and signature. The documents are then stored in an encrypted digital vault, providing the user with search-by-type capabilities along with digital assistance for the ongoing automated management of document content. The system does not allow copy-paste functions, and the unique identifier assigned to the document is embedded and encrypted, guaranteeing that no other version of the document is valid. Therefore, it delivers a single version of the digital document with 100% document integrity.The system is configured with a series of unique machine learning and artificial intelligence (AI) methods that operate under supervised, semi-supervised, and unsupervised frameworks.

Description

METHODS AND SYSTEMS FOR CONVERTING SINGLE-VERSION DIGITAL DATA AND DOCUMENTS WITH CONTENT MANAGEMENT DESCRIPTION Field of invention The invention generally relates to the conversion and digitization of all pre-existing data and documents and all newly created data and documents with a unique digitally created serial ID, assigned and audited or verified, which broadly guarantees the integrity of the data and documents. Single-version offering better methods in risk management, compliance management, financial performance management, and business, commercial, or enterprise management. Background Data is perhaps one of the most valuable assets in any business. Documentation is one of the most widely used tools for managing and communicating internal and external elements, such as, but not limited to, contracts, legal agreements, labor agreements, investment agreements, business rules, business processes, business decisions, business relationships, and financial performance. The integrity of documents is of paramount importance to businesses, as they govern internal and external relationships, decisions, opportunities, financial performance, risk, and compliance. Digitizing documentation is a progressive step toward ensuring document integrity while creating operational efficiencies and cost savings for the business.This is where the general technical capabilities and overall methodology of most systems that enable and support digital documentation have reached their limitations in both capacity and methodology. As such, there are opportunities to update how digital document content management and integrity are handled while delivering 100% document integrity. To achieve the aforementioned scenario for all types and formats of data and documents, and for all users and organizations, the computing device is configured to be interoperable with any data source and integration source. It digitally embeds a unique serial identifier (ID) in all data and documentation during the encryption process and is enabled by a range of artificial intelligence (AI) and machine learning methods to associate data, documents, business rules, and business recommendations, thus ensuring 100% document integrity for all users. The methodology and system capabilities for delivering 100% document integrity in the Single Version digital document model are already available.Furthermore, there are opportunities to offer users comprehensive document intelligence, automated document management, and the ability to prevent and eliminate 100% of all document forgery or fraud on a global scale. SUMMARY OF THE INVENTION Methods and systems for converting data and documents of any format and any type of data and document file into: a “Single-Version” of digital documents with content management; while completely eliminating problems and concerns regarding the integrity of the document content for all documents, while providing 100% document integrity. A first object of the invention is to provide a system and method for automatically reading, digitizing, storing and managing all data and documents in digital format. Single-version. Another object of the invention is to provide a single-version digital document that offers 100% document integrity. Another object of the invention is to provide document content management intelligence for all users. Yet another object of the invention is to provide a document containing an automatically generated serial identifier (ID) that is digitally embedded during encryption / encryption and is continuously audited. Yet another object of the invention is to provide a system for obtaining, consolidating, standardizing, automating, and analyzing all potential and existing document and data collection efforts. Another object of the invention is to streamline, simplify, and automate data analysis, data auditing, risk management, compliance management, and assessments. Yet another object of the invention is to provide a computing device that is based on a certain set of machine learning data analyzers to read the data and text information contained in documents and supply them to additional machine learning analyzers, called sub-analyzers, to further intelligently contextualize the data and text as they are converted into intelligent information and intelligent recommendations. Another object of the invention is to provide a system and method for clarifying and verifying the information that was imported into the system in comparison with the interpretation of the information processed by machine learning models. Yet another object of the invention is to provide a CIPBITS system based on various artificial intelligence (AI) and machine learning models that further contextualize what is happening within the user's data and documentation. The above objectives are achieved by providing a system comprising a computing or information device configured to: (a) receive documents, structured data, and unstructured data, in any format and file type, through user import; (b) verify and authenticate data and documents through integration methods; (c) read and digitize data and documents; (d) contextualize data and documents and present them on intelligent system dashboards and as actionable digital consulting advisories; (e) provide any type of information—good news, bad news, general news, actionable news, what works, what doesn't work, and recommendations—as intelligent information derived from all data and documents; and encrypt data and documents.(f) automatically create and assign a unique serial number identifier (ID) to each data file and document; a digital document vault for managing data and document content; (g) audit business financial and compliance performance, and manage document content outcome / performance / output; and (h) achieve single-version digital document content management. BRIEF DESCRIPTION OF THE FIGURES The features and advantages of the present inventions will be set forth in more detail in, or made obvious from, the following detailed descriptions of exemplary embodiments. The detailed descriptions of the exemplary embodiments are to be considered in conjunction with the accompanying drawings, in which similar numbers refer to similar parts and in which: Figure 1 is a block diagram of the user's document import process according to all the different document format types and document file types, according to some realizations; Figure 2 is a block diagram illustrating the initial utilization of the artificial intelligence (AI) system and machine learning methods through supervised, semi-supervised, and unsupervised machine learning, according to some realizations; Figure 3 is a block diagram that represents the management of document content and the different document phases that the system accommodates as it reads, digitizes, stores, and manages all data and documents as Single-Version digital documents, according to some realizations; Figure 4 is a block diagram illustrating how the system reads imported data and documents and what key elements the system is trained to read, according to some realizations; Figure 5 is a block diagram illustrating how the system digitizes imported data and documents and what key elements the system is digitizing, according to some realizations; Figure 6 is a block diagram illustrating how the system stores imported data and documents and what key elements the system is storing, according to some realizations; Figure 7 is a block diagram illustrating how the system manages imported data and documents, what key elements the system is managing, and how the system has reached its state of 100% document integrity of the “Single-Version” digital documents, according to some realizations; Figure 8 is a flowchart of an example method that demonstrates how the system's Single-Version digital documents reach their 100% document integrity state along with the content management carried out by the system in FIGURE 1. through FIGURE 7., according to some realizations; Figure 9 is a block diagram illustrating how the system architecture comprises the front-end and integration layer, working together with the intelligence layer, working together with the back-end and security layer in accordance with other realizations. DETAILED DESCRIPTION OF THE INVENTION The description of preferred embodiments is intended to be read in conjunction with the accompanying drawings, which are to be considered an integral part of the written description of these inventions. While the present invention is susceptible to various modifications and alternative forms, the specific embodiments are shown by way of example in the drawings and will be described in detail herein. The objectives and advantages of the claimed subject matter will become more apparent from the following detailed description of these exemplary embodiments in relation to the accompanying drawings. It should be understood, however, that the present invention is not intended to be limited to the particular forms disclosed. Rather, the present invention encompasses all modifications, equivalents, and alternatives that fall within the spirit and scope of these exemplary embodiments. The term "Single-Version Digital Documents" represents the single valid / certified / legitimate / legal version of the document, even if there are several different versions prior to digital signatures. The term "Single-Version Digital Documents" should be understood more generally as the only system and method that can offer users 100% document integrity and as the general term encompassing several of these exemplary embodiments.The term CIPBITS should be understood in a broad sense as a digital analyst and digital consultant who provides intelligent recommendations to users based on data and documentation that the user imports into the system and through system integration. The implementations described in this document are designed to automatically read, digitize, store, and manage all data and documents in a single-version digital format, offering 100% document integrity and intelligent document content management for all users. While some implementations, operating on a standalone, unique, and independent basis, may offer certain generic capabilities generally available to users, many of the described implementations are entirely unique, irreplaceable, and inimitable. For example, a document containing an automatically generated serial identifier (ID) that is digitally embedded during encryption and continuously audited enables comprehensive management of digital document content and provides 100% document integrity with the single-version approach. For example, organizations such as banks have certain business documentation requirements when considering providing capital to companies and businesses to which they have already provided capital. As a result, the bank has to receive documentation from various companies, often in different (and inconsistent) formats. Banks also have to manually analyze the information contained in the received documentation and, in some cases, manually enter information into pre-existing computer systems for asset and risk management. Examples of computing systems and devices of the present invention can obtain, consolidate, standardize, automate, and analyze, for the bank, all document and data collection efforts from each of its potential and existing business relationships.Following this activity, the computing systems and devices described herein can streamline, simplify, and automate data and document collection, data analysis, data auditing, risk management, compliance management, and financial performance evaluations for all companies that are potential or existing loan clients. This information is presented effectively in a user-friendly interface through the system's dashboards and the CIPBITS system. According to several implementations, exemplary multi-level systems can be used to assist in digital data analysis. For example, in some implementations, a computing device that relies on a particular set of machine learning data analyzers to read the data and text information contained in documents could invoke and rely on additional machine learning analyzers, called sub-analyzers, to further intelligently contextualize the data and text as they are transformed into intelligent information and recommendations before being presented to the user. In some implementations, the system's user interface provides a method for real-time user input related to the data and document import process. During this process, the user can clarify and verify the imported information by comparing it to the interpretation of the information processed by machine learning models. For example, when a user imports a document into the system for the first time, the system presents the user with a summary of key information. This summary comprises the key information obtained from the imported file, compared to the machine learning model's predictions in converting the imported data and documents into useful, contextualized, and intelligent information. In other embodiments, the CIPBITS system acts as a digital consultant for the user, complementing the digital analysis assistant capabilities described in the previous embodiments. CIPBITS are small, intelligent, and important pieces of information that a user can quickly and easily access through the system's user interface.Furthermore, CIPBITS is based on several artificial intelligence (AI) and machine learning models that further contextualize what is happening within the user's data and documentation, adding value to the user's data and documentation while answering what can be a very complex question that many users ask about their data, which is the why behind the activities and results to provide an intelligent retrospective view, current understanding and insight for future forecasting of what is working and what is not working for the respective user and business. Returning to the drawings, Figure 1 illustrates the workflow process, system capacity, and system design that enables users to import all pre-existing documents and all future documents into the system via the system user interface and integration for single-version digital document conversion, digital certification, and digital content management. The system supports importing all document format classes. For example, the system is not limited to any particular data and / or document type and format, but for illustrative purposes, the following is a list of common document format types that are supported by the system: all Microsoft document formats are supported, such as MS Word (.doc) (.docx), MS Excel (.xls) (.xlsx), MS PowerPoint (.ppt) (.pptx), and MS Notes; all Google document formats, such as Sheets; all text formats (.txt) and all CSV formats (.csv); all Adobe document formats, such as PDF (.pdi) and PSD (.psd); all image formats, such as PNG (.png), JPEG (.jpeg), and TIFF (.tif); all open-source documents from vendors such as LibreOffice (.odt); all XML formats (.xml); and all HTML formats (.html). In addition, the system supports various types of document and data files 118 for its users 102. The system is not limited to any particular type of data and document file 118, but for illustrative purposes, a list of file types is shown below. L77L iPI / iZi / E / YILI Common data and documents 118 that are compatible: Confidentiality Agreement, Term Sheets, Letter of Intent, Statement of Work / Project Details, Client Agreement, Supplier Agreement, Debt Issuance Agreement / Public Offering and Private Debt Offering, Loan Agreements, Stock Purchase Agreements, Investment Agreements, Purchase Orders, Invoices, Quarterly Cash Flow Statements, Profit and Loss Statements, Balance Sheet, Cash Flow Statement, Financial Reports, Employment Contracts, Independent Contractor Agreements / Service Provision Contracts, Corporate Operating Agreements, Corporate Capitalization Tables, Average Collection Period (ACP), Average Payment Period (APP), Accounts Receivable Aging Reports (APR), Accounts Payable Aging Reports (APR), Statements bank account statements, credit card statements,Business Financial Statements, Personal Financial Statements, Lease Agreements, Telephone Bills, Forms W-2, Personal Tax Returns, Personal Identification (Social Security Number, CURP #, Driver's License, Passport, Visa), Business Tax Returns, Business Identification (Tax Identification Number, IRS #) plus any document not specified above 120., As illustrated in Figure 1, data and documents can also be introduced through third-party integration 108. It is important to note that the system itself and its integration methods are neutral and agnostic, meaning that it can be deployed as a complementary solution for all users 102 and with each and every one of their existing systems. Figure 2 illustrates the high-level workflows 200 and capabilities 200 of Single-Version digital documents 202 along with the various machine learning methods the system uses to read, digitize, store, and manage all data 304 and all documents 306 imported 104 by users into the system 102. The system uses three levels of machine learning in realizing its Single-Version digital document capabilities 202. The first method is supervised machine learning 208. The supervised machine learning method 208 incorporates real-time human interaction with the artificial intelligence through the system's user interface 106 so that the user can clarify 210 and verify 212 that the machine has identified all key terms 406, all key fields 404, and all key parts 408.User interface 106 shows users what the system has predicted, compared to the actual file that user 102 imported, for user 102's security, data accuracy, and document accuracy. The system offers this machine learning layer to its users 102 after the initial data and document import 104. In this step, user 102 will clarify 210 any missing information from the system; then, user 102 will verify 212 that the system has predicted correctly. User 102 will then update 214 any elements that need updating to further monitor and train the machine in real time so that all system predictions are accurate from that point forward.During these 208 supervised machine learning steps, the system creates a digital record of the user's interaction 102; simultaneously, this interaction is stored 218 in the activity ledger 410 for future intelligent recommendations. This user interface capability 106 ensures the accuracy of the information presented on the system dashboards. Once the imported information has been clarified 210, verified 212, and updated 214, users will save 216 everything, and the system will record and log any user-defined changes and store 218 these for future data and document imports 104. The second method is semi-supervised machine learning 222. This method combines a hybrid of user-entered information 102 with machine-recognized and generated inputs.This method begins by performing automated self-adjustments and then automatically monitors and audits the accuracy of these adjustments. The third method is unsupervised machine learning. This method requires no interaction between the end user and the system or between the technical support team members and the system. This advanced artificial intelligence (AI) and machine learning method enables the system not only to perform statistically accurate edits and updates of various types of document and data files, but also to enable digital analysis and digital advisors to provide digital consulting recommendations to the user via CIPBITS. The monitoring of these intelligent CIPBITS recommendations and the user's decisions is handled and updated in a unique, automated, and unsupervised manner within the embedded computing device.It is worth noting that the ability to allow the embedded system's artificial intelligence (AI) and machine learning models to interact in real time with end user 102 is unprecedented in any other non-embedded computing system or device in these inventions. This provides on-demand feedback to both the end user and the system itself for real-time machine learning and instant training of AI models. This interaction between user 102 and the machine also helps build trust and verification between user 102 and the system, enabling the machine to be used and trusted by user 102 as a capable and intelligent digital assistant.These are very unique features of the system and user interface 106 that are implemented in all layers embedded in the system within the computing device that allow complete digital management of 220 capabilities and “Single-Version” digital documents with 100% document integrity 712. Figure 3 illustrates how the system provides content management 300 of single-version digital documents 302 by reading 204, digitizing 206, storing 208, and managing 210 all data 304 imported 104 into the system and all documents 306 imported 104 into the system. The system's digital content management capabilities 300 go far beyond traditional methods of creating digital documents by offering digital analytics, digital auditing, and digital consulting assistance through CIPBITS 224. Figure 3 further describes how the system manages the content of a document regardless of the stage 308 the document is currently in, such as the template form / format 310, the completed form / format 312, the signed form / format 314, the pre-existing 110, and all new documents 112 that the user 102 will create within the system.The activity ledger 410 in Figure 4 monitors and audits the user's edits 506 as the data and document progress through its lifecycle and document phases 308. The "Single Version" digital document content management 302 is made possible by the system's reading of all data 402, the digitization of all data 502, the storage of all data 602, and the management of all capabilities 702, which are then made available to users 102 through the user interface 106 and the CIPBITS system 224. As can be seen, a system that provides data and document intelligence with continuous content management that offers digital intelligence assistance to the user 102 is unique and one of a kind. The systems and methods of the present invention, therefore, offer unprecedented data and document integrity combined with data and document content management 302 for the user 102.Returning to Figure 4, the ability to read all (402) is the first of four main functions that provide the user with single-version (302) digital document content management with 100% document integrity (712). This provides the highest level of insight (400) and capabilities (400) demonstrating the supervised method (402). As shown, the read function (204) focuses on all data (304) and all documents (306), while identifying and contextualizing all key fields (404), key terms (406), and key parts (408) included in the data and documents. Because the system reads all (402) functions are automatically executed when importing data and documents (104), the activity ledger (410) is automatically executed during the verification and authentication (414) of data and documents.The verification methods 412 and authentication 414 of data and document content integrity are uniquely performed in an additional layer of automation of what is traditionally a very manual process for the user 102, while complementing the encryption methods 416 and the creation 420, assignment 422 and continuous digital auditing 424 of the unique serial ID 418 for each data set and document that guarantees 100% document integrity 712. As shown in Figure 4, CIPBITS 224 is being leveraged by the read all function 402 to digitally assist the user with intelligent advisors 230, as the read all function 402 is being executed and presented to the user 102 in a very user-friendly and acceptable format. Referring now to Figure 5, as we saw at the highest level of vision 500 and capabilities 500, the ability to digitize everything 502 is the second of the four main functions that deliver to the user the management of digital document content “Single-Version” 302 and with 100% document integrity 712. It is worth highlighting and drawing attention to the methods for converting all data 304 and all documents 306 into digital format to fully digitize 206 all key fields 404, all user edits 506 and all signatures 508 for proper storage 616 as shown in Figure 6. Returning to Figure 5, since the digitize all function 502 is being executed; the system is automating, standardizing and consolidating 510 all data 304 and all documents 306 into user interface panels 106 and CIPBITS 224, enabling connectivity 512, transparency 514 and accountability 516 for all data 304 and all documents 306 activity 610 as shown in Figure 6 for system users 102. As a result of such comprehensive data and document analysis 112 and content contextualization 610, business compliance management 502 is fully automated. The second of the three main categories is document compliance 510. Document compliance 510 focuses on all key fields, key terms, and key parts within the content of each document. Most companies manually monitor 626 and audit 628 the risk and compliance 716 related to document content as it pertains to business activity, commercial performance, and financial performance.Furthermore, most companies do not have a good system or method for monitoring 626 and auditing 628 document integrity; however, the computer device incorporated in this present disclosure is capable of automating all of this for users 102 as a result of such data and document analysis 112 and, as such, content contextualization 610, document compliance 716, and document integrity are fully automated. The third of the three main categories is third-party compliance 518. Third-party compliance 518 focuses on the customer 520, the supplier 522, and all other 524 external business relationships that require documentation to consummate and manage the relationship.Most companies manually monitor 626 and audit 628 to detect risks and compliance failures 716 with respect to third-party activities and processes; however, the computer device incorporated in this present disclosure is able to automate all of this for users 102 as a result of this comprehensive analysis of data and documents 112 and the contextualization of content 610 as such, third-party compliance management 518 is fully automated. Turning now to Figure 6, the ability to store all of the 602 at the highest level of vision 600 and capabilities 600 is the third of the four main functions that offer user 102 “Single-Version” digital document content management 302 with 100% document integrity 712. The example of pre-existing document management 108 is of singular importance to users 102, as it relates to the cost of using the system to manage all legacy data and documents. These self-service capabilities available through the system's user interface 106 eliminate the initial setup and implementation cost for user 102. This is a remarkable feature, enabling all users 102 and any business within any industry of any size to implement the embedded system with zero setup and implementation fees. Turning our attention back to Figure 6.Examples. In addition to the pre-existing example 108, the system storage function 216 is maintained by capturing all user edits 506 and signatures 508, while all document data and activity 610 is routed to encrypted storage 416 616. Additional examples of activity management 610 that the system supports for all users 102 and all parties 614 included in documents are the storage 616 of key dates 612, key terms 406, activity ledger information 410 in the primary database 618, data lake 620, and data vault 622. Within the data warehouse 622, user 102 can utilize search-by-type capabilities for efficient data and document retrieval and data and document lifecycle management. Figure 7 illustrates the management of all 702, which is the fourth main function that the system uses to deliver to user 102 the management of digital document content with a “single-version” 302 and 100% document integrity 712. In accordance with the first three main functions represented from Figure 4 to Figure 6, the management capability of all 702 encompasses the management of all data 304 and all documents 306 for user 102. As a result of all data 304 and all documents 306 being read 204, digitized 206, and stored 208, the system is able to efficiently manage 220 all data and documents in workflow 704, user editing 506, and activity 610, while providing users 102 with smart notifications 706 and a digital activity log 410 that enables intelligent content management.Furthermore, by way of example, the system does not allow copying / pasting 708 of any data or document, nor does it allow taking any screenshots 710. Each and every one of these activities mentioned above would historically result in potential risks or breaches; however, as a result of the aforementioned capabilities of the “Single-Version” digital document system 202, and the integrity within the function of managing everything 702, these potential risks and breaches are completely prevented from occurring. Therefore, the user is offered 100% integrity of the Single-Version digital document 712. As we saw in the highest level of vision 700 and capabilities 700. Figure 8 provides a summary-level overview of how the system and methods described in Figures 1 through 7 offer users single-version content management and single-version document integrity. For the user to initiate the system's capabilities and methods, it begins with the system receiving data and documents. The next progressive step in the flowchart is the system applying artificial intelligence (AI) and machine learning methods to intelligently read, digitize, store, and manage all data and documents.Moving forward in the flowchart, the encryption and data filling for storage 806 provides the user 102 with data and document security and user interface 106 access to subsequent data and document content that was contextualized and summarized in the system panels and CIPBITS 224. The embedding of a unique ID 808 is a very strategic function of the system that enables “Single-Version” digital documents 202. For the reader's context; the system creates 420, assigns 422 and audits 424 the embedded unique ID 808 and the word unique is intentionally used in the method of creating 100% document integrity 814 for all users 102.As the system digitally manages, monitors, and audits all content 24 / 7 / 365, users can have the statistical and digital peace of mind that all risk and compliance elements related to data and document content management have intelligent, machine-driven oversight, full awareness, and foresight working on their behalf. Figure 8. Examples of the flowchart Single-Version with content management 812 and 100% integrity of the document “Single-Version” 814. These last two examples in Figure 8, the flowcharts are the culmination of the system features and functions and the methods incorporated in the present invention. Continuing with Figure 8, for the sake of thoroughness and in summary, all the methods incorporated within this unique system for intelligently and digitally managing all data (304) and all documents (306) result in a number of valuable and unique capabilities for User 102. As noted earlier, most User 102 operate their business with more than one system, and in most cases, those systems are not integrated with each other. This means that User 102's ability to derive maximum value from their data and the content within their documentation is very limited. The system and methods incorporated from Figure 1 to Figure 8 have eliminated these limitations for User 102 while offering single-version digital document content management (302) and 100% document integrity (712). Figure 9 provides a high-level overview of the system's architecture (902) and outlines the three primary layers that work together to enable the system and methods incorporated in this disclosure. It is worth noting that while each layer within the system's architecture (902) is structured and performs independent functions for users (102), each layer is complementary to the others and works in unison to support and deliver single-version digital documents and content management (302) and 100% document integrity (712). Continuing with Fig. 9, the front-end and integration layer 904 corresponds to the area within the system architecture 902 where users 102 are able to interact with the Single Version digital documents and content management 302 through the self-service API(s) 906 to digitally connect with external data sources and import data and documents 104. The front-end and integration layer 904 initiate and feed the system's intelligence layer 908, which is where all data 304 and all documents 306 are read 204 and digitized 206 through the system's supervised 208, semi-supervised 222, and unsupervised 232 AI (artificial intelligence) and ML (machine learning) models 910.All data 304 and all documents 306, once read 204 and digitized 206, are presented in the web logic components 912 where the additional data analyzers 226, sub-analyzers 228, and intelligent analyzers 914 reside. The unique and specific methods of how the system uses the analyzers 226, sub-analyzers 228, and intelligent analyzers 914 as groups of analyzers that support each other to further contextualize all data 304 and all documents 306, allow data from multiple data sources to be transformed into useful and intelligent information and presented to users 102 through CIPBITS 224.As all data 304 and all documents 306 are imported 104 and / or integrated into the system via the API(s), the system architecture 902 is simultaneously presented to the intelligence layer 908 and the security and back-end layer 916 for encoding 918 and storage in databases I and II 922 together with data lake I and II 924. Once the intelligence layer 908 has contextualized all data 304 and all documents 306 and converted them into information, the information, along with all data files 304 and all document files 306, is digitally stored 218 in the digital vault 926 for categorization of information and digital document files 202 of Single Version, storage 218, and management of Single Version digital content 812. It is important to highlight that the flow of all data (304) and all documents (306) into the system architecture (902), through the layers of the system architecture (902), and back to users (102) are all taking place simultaneously and in conjunction, which is a perpetual recurring cycle of all data (304) and all documents (306) entering the system for Single Version digital documents and content management (302) for digitization, conversion of Single Version digital documents (202), with systematic management / administration capabilities, monitoring and auditing all content (810) for users (102) while delivering the Single Version that has 100% document integrity (814). One last unique method incorporated in this disclosure that is worth highlighting is the self-service encryption multiplier (920) that the system provides to users (102).Data security is paramount for the entire industry, so when a user 102 would like to see encryption for all data 304 and all documents 306 with encryption greater than 256 bits option 918 the methodology and capacity of the system allows users 102 to write their own encryption multiplier 920 which increases the bit encryption exponentially based on the multiplier entered by the users 102, making the Single Version digital documents 202 even more secure, in addition to the “single version” digital document and content management 304 which offers a “single version” that has 100% document integrity 814 and digital analyst 114, digital consulting 118 and digital assistant 122 capabilities through CIPBITS 124.

Claims

1. A system comprising: a computing or information device configured to: - receive documents, structured data and unstructured data, in any format and file type, through user import; - verify and authenticate data and documents through integration methods; - read data and documents; digitize data and documents; contextualize data and documents; and present data on intelligent system dashboards and as actionable digital consulting advisors; - provide any of the following as intelligent information derived from all data and documents: good news, bad news, general news, actionable news, what works, what doesn't work, and recommendations; - encrypt data and documents; - automatically create and assign a unique serial number identifier (ID) to each data file and document;and generate a digital document vault for managing document data and content; - audit the business's financial and compliance performance, and manage the outcome / performance / output of document content; - achieve single-version digital document content management and 100% single-version document integrity.

2. The system in accordance with claim 1, characterized in that the received document comprises any data and file format and any data and file type.

3. The system of claim 2, characterized in that the types of data and document files and the types of format are received through import by users through “self-service” available in the system user interface and through any third-party integration.

4. The system of claim 1, characterized in that the reading of data and documents comprises a series of machine learning and artificial intelligence (AI) methods used to contextualize and convert data and text into actionable information.

5. The system of claim 1, characterized in that the digitization of the data and documents comprises a series of machine learning and artificial intelligence (AI) methods used to identify the data and the type of document to be read and convert them all into digital format.

6. The system of claim 1, characterized in that the contextualization of the data and documents comprises a series of machine learning and artificial intelligence (AI) methods used to identify the key terms within the document, understand and contextualize the key parts within the document, understand and contextualize the key dates within the document, and understand and contextualize the signatures (or missing signatures) within the document.

7. The system of claim 6, characterized in that the key terms, key parts, key dates, signatures (or missing signatures) comprise a series of machine learning and artificial intelligence (AI) methods used to digitally assist the user in managing all actionable elements within the data and documents.

8. The system of claim 1, characterized in that the computing device is configured to further contextualize the data and documents and present the data as actionable information through digital consulting advisors called CIPBITS.

9. The system of claim 1, characterized in that the encryption of data and documents comprises an industry-standard 256-bit method with a user-defined encryption bit multiplier within its own interface, will have the possibility of self-defining additional layers...] which offers additional layers of user-defined data and document encryption.

10. The system of claim 1, characterized in that the computing device is further configured to automatically generate and automatically assign a unique serial number identifier (ID) to each document, creating the Unique Version of the document.

11. The system of claim 10, characterized in that the computing device is configured to automatically embed the unique serial number identifier in each document, while completely eliminating all forms of document replication.

12. The system of claim 1, characterized in that the computing device is configured to store all data and documents in a digital document vault that offers search-by-type and digital management of all data and documents.

13. The system of claim 1, characterized in that the computing device is configured to audit the performance / behavior / outcome of the document content and determine whether all the document content is being completed fully and correctly. L77L iPi / iZiZ / E / Yili 14. The system of claim 13, characterized in that the computing device is further configured to manage all terms within documents, contract-related documents, finance-related documents, and operations-related documents for users through a series of machine learning and artificial intelligence methods and intelligence dashboards and alert notifications to protect against all breaches of contract and the risk of financial and business / commercial / business performance.

15. A system comprising a computer configured to: receive data and documents in any format and any file type through user import and integration; read any format of data and documents through artificial intelligence (AI) and machine learning methods; convert and digitize data and documents; store data and documents in a document vault for digital document management; encrypt / cipher data and documents; and create a unique serial number identifier (ID) and assign it to each encrypted / ciphered document for digital document content management, ensuring single-version and 100% document integrity.

16. The system of claim 15, characterized in that the Single-Version digital documents allow 100% document integrity and the management of the content of the digital documents to safeguard and protect all data, contracts and terms of performance / execution of the documents, on behalf of the users.

17. The system of claim 16, characterized in that the digital document content management uses a series of machine learning and artificial intelligence (AI) consulting advisors (CIPBITS) to compare all data elements with all business rules with all information contained in the data and documents (entered) to digitally assist with compliance management, risk management and performance management for the user.

18. The system of claim 16, characterized in that when a Single-Version digital document is used, it is the only type of document that offers the user 100% document integrity and digital document content management.

19. A method implemented in a system comprising a computer computing device, comprising the steps of: a) receiving data and documents in any format and any file type through user import and integration; b) reading any format of data and documents through artificial intelligence (AI) and machine learning methods; c) converting and digitizing data and documents; d) storing data and documents in a digital document registry or vault for digital document management; e) encrypting / ciphering data and documents; and f) creating a unique serial number identifier (ID) and assigning it to each encrypted / ciphered document for digital document content management, ensuring a single version and 100% document integrity.

20. The method of claim 19, characterized in that the reading of the data and document format is performed through a supervised machine learning method.

21. The method of claim 19, characterized in that the reading of the data and document format is performed through a semi-supervised machine learning method.

22. The method of claim 19, characterized in that the reading of the data and document format is performed through an unsupervised machine learning method.

23. The method of claim 20, characterized in that the supervised machine learning method incorporates real-time interaction with artificial intelligence through the system's user interface. 24.- The method of claim 23, characterized in that the supervised machine learning method deploys the system's prediction in comparison with the actual imported file.

25. The method of claim 24, characterized in that the supervised machine learning method generates a digital record of the user interaction in the activity ledger, for future intelligent recommendations.

26. The method of claim 21, characterized in that the semi-supervised machine learning method combines a hybrid of user-provided information with inputs recognized and created by the machine or system.

27. The method of claim 22, characterized in that the unsupervised machine learning method employs an advanced artificial intelligence method, does not require interaction with a user, and provides recommendations through digital analysis and digital advisors to the user.

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