Submission type
UiPath for Coding Agents
Name
Abhishek Jagtap
Industry category in which use case would best fit in (Select up to 2 industries)
Finance
Complexity level
Advanced
Summary (abstract)
This Invoice Extraction Bot automatically processes PDF invoices by reading files from a folder, pushing them into an Orchestrator queue, extracting key invoice details like invoice number, date, total amount, and tax using Regex, and storing the structured data into Excel. Built using UiPath Studio REFramework and AI-assisted prompting, the solution demonstrates how agentic automation can accelerate enterprise workflow development while reducing manual effort and improving processing accuracy.
Detailed problem statement
Many organizations still process invoice PDFs manually, where employees open each invoice, identify important fields like invoice number, invoice date, tax, and total amount, and then enter the data into Excel or ERP systems. This process is repetitive, time-consuming, error-prone, and difficult to scale when invoice volumes increase. The challenge is to build an automated and scalable solution that can intelligently process multiple PDF invoices, extract structured invoice data accurately, manage transactions reliably through queues, and maintain proper logging and exception handling using enterprise-grade automation practices in UiPath Studio.
Detailed solution
The solution is built using UiPath Studio REFramework to create a scalable and enterprise-ready Invoice Extraction Bot capable of processing multiple PDF invoices automatically. The automation begins by reading configuration values such as folder paths, queue names, and output file locations from Config.xlsx to ensure maintainability and avoid hardcoded values. The bot scans the Test folder recursively to identify all PDF invoices and validates the availability of required resources such as the invoice folder, Excel output file, and UiPath Orchestrator connectivity.
Once the files are identified, the automation creates or validates the existence of an Orchestrator queue named InvoiceProcessQueue. Each PDF invoice is then added as a separate queue transaction containing metadata such as file name and file path. Using queue-based processing enables transaction isolation, retry capabilities, monitoring, and scalable execution across multiple robots if required in the future.
During transaction processing, the bot retrieves one queue item at a time and reads the content of the PDF invoice using PDF text extraction activities. Instead of relying on fixed templates, the solution uses Regex-based extraction logic to dynamically identify important invoice fields such as Invoice Number, Invoice Date, Total Amount, and Tax Amount. This approach makes the automation flexible enough to handle invoices with varying layouts and formats.
The extracted data is structured into a DataTable and appended into main.xlsx under the InvoiceData sheet. If the Excel file or worksheet does not exist, the bot creates them automatically along with predefined headers. The solution also captures transaction status, timestamps, and detailed error messages to maintain proper auditability and reporting.
To ensure reliability, the automation follows REFramework best practices with proper initialization, transaction handling, logging, and exception management. Business exceptions such as missing invoice data or invalid PDF content are handled separately from system exceptions such as file access issues or Orchestrator failures. Detailed logs are generated throughout the process to provide complete visibility into queue creation, transaction execution, extraction results, Excel updates, and failures.
Additionally, the solution leverages AI-assisted prompting using Codex and UiPath Skills to accelerate development by generating workflows, queue logic, Regex patterns, and REFramework modifications directly through prompts inside UiPath Studio. This demonstrates how Agentic Automation can significantly reduce development effort while still maintaining enterprise-grade automation standards.
Narrated video link (sample: https://bit.ly/4pvuNEL)
Expected impact of this automation
The automation is expected to significantly reduce the manual effort involved in invoice processing by eliminating repetitive tasks such as opening PDF invoices, extracting data manually, and updating Excel sheets. By automating the entire workflow using UiPath Studio and UiPath Orchestrator, the solution improves processing speed, increases data accuracy, and minimizes human errors commonly caused during manual data entry.
The queue-based REFramework architecture ensures the solution is scalable, reliable, and capable of handling large volumes of invoices efficiently with proper transaction tracking and retry mechanisms. Automated logging and exception handling provide better operational visibility and easier troubleshooting, while structured Excel reporting enables faster downstream processing and auditing.
Additionally, the use of AI-assisted prompting and Codex inside UiPath development showcases how Agentic Automation can accelerate bot development cycles, reduce implementation effort, and enable faster delivery of enterprise automation solutions.
UiPath products used (select up to 4 items)
UiPath Automation Cloud™
UiPath Studio
Automation Applications
PDF, Excel
Integration with external technologies
No
