Cognitive Automation
for Invoice Entry

Reduces running costs and errors simultaneously.

Description of Problem

High-Volume, Manual Invoicing & Approvals: Time-consuming, error-prone 

The client manually processes more than 500 invoices each day. They receive invoices from multiple vendors in different formats like PDFs and scanned graphic files. The team needs to download and save each invoice from various sources, including email and vendor portals.

Although the client was using an existing application to extract metadata from invoices, it was not reliable. It still required team members to manually extract invoice data, enter that data into a database, and route the invoices to approvers, requiring manual verification of several documents. The process for Finance staff to approve invoices, which required team members to compare data from multiple systems, was time-intensive, slow, and error-prone.

Client Overview:

Sunlun is a Malaysian Tyre Distributor & Automotive Products Supplier. They involved in sales and distribution of tyres, tubes, flaps, batteries, rims, automotive/industrial lubricants, workshop equipments and other related products throughout Malaysia.

Industry:

Logistics/ Supply Chain/ Distribution

Processes Type:

Invoice Entry

How Gleematic Helps

New Invoices Detection

Gleematic can check and monitor incoming emails, detect any new invoice coming through the system, and download these into specific folder(s).

Data Extraction

After finding new invoices, Gleematic will extract data from invoices and place data points into Excel sheet. (e.g. Invoice Number, Date, Total amount, and Supplier's name). It is also able to check for data integrity and missing data.

Data Entry

Gleematic copies the extracted information about the invoices from Excel and enter these into the accounting system. Gleematic types “DONE” on the Excel file to let human know which invoice has been processed.

Results

neuromorphic-computing

Degree of Robotization: 75% Effort Automated

financial-statement

ROI: 3 Months

Human Error Rate Reduced

tester

Manual Effort Reduction to 75%

real-time

Faster Processing Time: Reduction of 65%

workflow

More Standardization

information-technology

High-Quality Improvement

working-hours

No More Repetitive Administration

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