Robotic Budget Data Extraction for Accurate Database Population

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Solution Overview

Problem

Large organizations face significant challenges in accurately and efficiently converting budget documentation, such as procurement and R&D-specific budget books, into tabular data for database population due to the incompatibility of native formats and the introduction of errors through manual or computer-generated conversions.

Innovation Solution

Implementing programmatic robotic processes that convert data from native formats like PDF to tabular data using virtual machines and programmatic bots, which interact with document and database applications to automate the data extraction and population process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual or computer-generated conversion methods are used to convert budget documentation from native formats to tabular data, then the conversion process can be completed, but errors are introduced and accuracy deteriorates

Engineering Contradiction:

Improveconversion speedVSAvoiddata accuracy

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

The system enables self-service by allowing the budget documentation to be converted automatically through robotic processes that extract and transform data without human intervention, eliminating manual errors while maintaining high conversion speed and accuracy

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical conversion processes with automated robotic software processes that use optical character recognition and data extraction algorithms to convert budget documentation, substituting human labor with programmable systems that maintain both speed and accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Manufacturing precision

If programmatic robotic processes are implemented to automate data extraction and conversion, then accuracy and efficiency improve, but system complexity increases

Engineering Contradiction:

Improvedata accuracyVSAvoidsystem complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The robotic process automation system performs multiple functions including data extraction, format conversion, validation, and database population through a single integrated platform, reducing the need for multiple separate systems and tools while maintaining high accuracy

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent introduces an intermediary robotic software layer that bridges the gap between native budget documentation formats and tabular database formats, handling the complex conversion processes through standardized interfaces and reducing direct system-to-system complexity

Inventive Principle:

Principle #24Intermediary (Mediator)

3Device complexity

If traditional manual conversion methods are used, then system complexity remains low, but time consumption and labor effort increase

Engineering Contradiction:

Improvesystem simplicityVSAvoidconversion time

Core Design Contradiction:

Device complexityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by pre-configuring robotic processes with extraction rules, transformation logic, and validation criteria before conversion begins, enabling automated high-speed processing without requiring complex real-time decision-making during execution

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent changes parameters by transforming data from one format structure to another through programmable conversion rules, allowing rapid automated processing while maintaining simplicity through standardized transformation parameters rather than complex custom logic

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20260099471A1Dynamic management and population of databases using programmatic robotic processes

Publication Date: 2026.04.09 THE TORONTO DOMINION BANK

AI summary

The disclosed embodiments include computer-implemented apparatuses and processes that dynamically manage and populate databases using programmatic robotic processes. For example, an apparatus may obtain queued request data including a key code and a program code associated with a resource. Based on that key code, the apparatus may obtain files of a first format. The apparatus may also extract elements of resource data that include the program code from one of the files, and convert the extracted elements of resource data into elements of tabular data structured in a second format. The apparatus may, based on the elements of tabular data, generate elements of a populated database associated, and transmit message data that includes the elements of the database to a device, which may execute an application program that presents a subset of the elements of the database within a digital interface.