Customer Story
How Valtatech streamlined Invoice Processing using Docsumo
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About the customer
Valtatech is a managed services provider based inMelbourne, 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
enterprises served
100+
Documents processed
20,000+
per Month
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 layout is 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 trasaction 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.
unstructured Data.
99%
Touchless processing using smart validation rules
65%+
Processing cost reduced by
automating workflow end to
end
automating workflow end to
end
Ready to automate your data extraction?
Let's talk.
Docsumo's intelligent document processing enables you to extract data easily, efficiently, and accurately.
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