Customer Story

How Valtatech streamlined Invoice Processing using Docsumo

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Using Docsumo turned out to be a real game changer for us.

“Bringing down the invoice processing time from a few hours to less than 5 minutes with 99% accuracy has been a real-game changer for us. With Docsumo’s help, we have been able to automate invoice processing resulting in lower turnaround time and better customer experience.”

Jussi Karjalainen

Founder & Managing Partner, Valta Technology Pty Ltd

About the customer

Valtatech is a managed services provider based in Melbourne, Australia working with over 60 enterprise customers helping them with digital transformation of their procurement, accounts payable and payment processes.
Industry
Managed Services
Company size
100+ Employees
Portfolio Units
100+
Document Processed
20,000+ per Month

The case study: In a nutshell

Before

Manually scanning unstructured invoices
A team of 20+ back office staff process 20,000+ invoices on a monthly process
Scanning data from 100+ invoice types from 100+ different vendors manually is cumbersome
Little to no validation done on captured data
All documents had to undergo double manual entry

After

Capture data from unstructured documents with smart AI-based APIs
Employees review only exceptions
All the variations in the layout are taken care by ML-based smart data extraction API
Docsumo's algorithms auto-classify letters and validate data with custom rules in real-time
95%+ straight through processing

The Challenge

Process unstructured invoices

  • Valtatech collects data from varying invoices received from 60+ enterprise customers.

Identify & classify invoices

  • Valtatech needs to classify and categorize data from different types of invoices
  • Data to extract includes transaction details and key-value pairs consisting of company details

Capture data from invoices with 60+ layouts from 60+ enterprises

  • Not only did the structures vary for different invoices but the position of data to capture varies for these documents
  • Some of them has nested tables as a part of transaction details

Categorize & derive attributes from extracted data

  • The manual extraction lacked a logical validation of payment and transaction details.

The Docsumo Solution

Ingesting invoices to the API

  • API-based direct integration that seamlessly ingests invoices onto Docsumo.

Pre-processing and getting ready for data extraction

  • Inbuilt document pre-processors identified the letter formats (JPG, PDF, PNG etc.) and queued them up for data extraction.

Data extraction from unstructured text

  • Docsumo's OCR module used the vectorized position reference in a letter to extract data.
  • The OCR not only parsed through letters with varying fonts, layouts, image quality, and resolution; it even extracted data from the tables with 95%+ accuracy.

Intelligent categorization of key value pairs

  • Our proprietary NLP-based classification framework started rapidly learning from all the documents. It was trained to categorize key value pairs and line items.
  • Another algorithm started making intelligent predictions to identify the data within an invoice.

Rule-based data validation

  • Once the data is extracted, a rule-based validation engine applied contextual data validation and correction algorithms.

Integration with downstream software

  • The data was extracted in a JSON format that was easily integrated into downstream bill payment software via APIs and iframe.

Result: 99%+ Data extraction accuracy

<30sec
Processing time of unstructured Data.
99%
Touchless processing using smart validation rules
65%+
Processing cost reduced by automating workflow end to end
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