Accelerating Finance Operations: How AI-Powered Invoice Automation Boosted Processing Efficiency by 80%
Challenges
1- Manual Entry: High effort in downloading and entering invoice data.
2- Unstructured Formats: Inconsistent vendor invoice layouts.
3- Error-Prone: Frequent manual errors and rework.
4- Low Scalability: Hard to onboard new invoice types/vendors.
Solutions
1- Email Automation: Used Outlook API to auto-download invoice attachments.
2- AI Extraction: LLMs extracted key data from unstructured PDFs.
3- Salesforce Integration: Selenium bots auto-filled invoice data.
4- Daily Reports: Monitored invoice status for better control.
5- Smart Feedback Loop: Improved accuracy with ongoing learning.
Results
1- 80% Faster Processing
2- 70% Lower Operational Costs
3- 35% Higher Data Accuracy
4- Real-Time Financial Visibility
5- Easily Scalable Invoice Handling
A leading distributor in the tile and flooring industry was managing a large volume of vendor transactions within Salesforce. However, the absence of automation in their invoice processing workflows was creating operational inefficiencies and limiting scale.
The finance team encountered daily bottlenecks due to manual invoice processing, inconsistent formats across vendor submissions, and frequent data entry errors. These issues hindered reconciliation speed and reduced the overall agility of financial operations.
To eliminate these inefficiencies, we deployed an AI-powered automation framework that continuously monitored invoice emails, leveraged Large Language Models (LLMs) to extract structured data, and seamlessly pushed that data into Salesforce using Selenium-based automation. This solution accelerated processing, enhanced accuracy, and significantly reduced operational overhead.
- Manual Invoice Processing: Our client’s finance teams manually download, review, and enter invoice data into Salesforce, which consumed significant time and effort.
- Unstructured Data Formats: Vendor invoices arrived in varied formats—making it difficult to extract and organize the data consistently.
- Error-Prone Workflows: The lack of automation resulted in frequent data entry errors, requiring rework and delaying reconciliation.
- Scalability Limitations: Adding new invoice types or vendors required major process adjustments, limiting operational agility.
- Email Monitoring with Outlook API: Integrated the Outlook API to automatically scan for invoice emails and download attachments hourly.
- AI-Powered Data Extraction: Deployed LLMs to intelligently extract structured data from unstructured PDFs, covering key fields like PO/SO numbers, invoice date, amounts, and line items.
- Automated Salesforce Integration: Used Selenium-based bots to input extracted invoice data directly into Salesforce with minimal human intervention.
- Daily Performance Reporting: Built daily summary reports showing processed, failed, and pending invoices—enhancing transparency and control.
- Continuous Learning & Error Handling: Implemented a feedback mechanism to log failed invoices and refine extraction accuracy over time.
80%
Faster Invoice Processing
Automated workflows drastically reduced processing time and manual intervention.
70%
Reduction in Operational Costs
Savings achieved through decreased resource involvement and faster cycle times.
35%
Increase in Data Accuracy
AI-powered extraction minimized human errors, improving data integrity.
Improved Financial Visibility
Real-time data updates in Salesforce enhanced reporting and decision-making.
Scalable Invoice Management
New invoice formats can now be onboarded without major system rework.
