Invoice Processing Automation
Automate Invoice Processing with AI. Process invoices in less than one-fifth of the time required when processing manually, manage your end-to-end AP workflows with ease by seamlessly ingesting invoice data across multiple channels.
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Cost Savings
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Lower setup costs
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Lower TCO
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Accuracy with AI
Intelligent automation that transforms invoicing processes with best-in-class performance
Features Compared: KlearStack AI V/s Template-based Invoice Data extraction.
Let us see what makes KlearStack the best software for invoice processing automation. Here we compare the top invoice automation solutions in the industry that require users to draw templates, i.e. the boxes around invoice details in order to get trained. Also read how KlearStack is purely AI based algorithm that overcomes these limitations.
| Template-based solutions | KlearStack AI |
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User needs to define templates for each different layout of invoices and this takes time.
E.g. if there are 1000 variation of invoices, you need to define 1000 templates. |
No templates needed. Extracts data using Deep Learning models. |
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It takes time to define templates.
E.g. For 1000 invoice layouts, it will take approx. 500-700 person days to define all the templates. |
User saves the template definition time and effort, since no templates need to be defined. |
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Slight change in invoice layout needs to retrain template, which is not scalable.
E.g. Supplier name position changes from right to left part of invoice. |
Machine Learning models handle the data extraction even if the invoice layout changes. |
| Need trained resources for defining or modify templates. | You don’t need specially trained template developers |
| Up-front license required per template developer |
No license. Default business model is SaaS.
Only subscription fees need to be paid (based on usage) |
| Setup process is tedious. For ex: Flexicapture needs to be installed along-with the pre requisites on every template developer’s PC | SaaS delivery model. Hence nothing needs to be installed locally. However, On-Premise option also available, if required. |
| Line items with multiple span will not get properly extracted. | Intelligent extraction of line items, irrespective of the span. |
| Supports multiple languages, since this relies on templates. | KlearStack supports English currently. ML models can be trained for additional languages. 2+ person-weeks of effort for each language. Multiple languages can be trained within short span of few weeks. |
Benefits of AI-driven Invoice processing Automation
Enjoy benefits of economies of Scale, by digitizing and automating end-to-end Invoice processing Workflows. Leverage AI and NLP for not only data extraction, but also data interpretation, data processing and automated Invoice Processing Workflows.
Intelligent Scanning
Reduced Manual Data Entry
Extract data via intelligent scanning and dynamic reproduction, reducing the time and efforts taken to type. The scanner and pattern recognition features, easily identify patterns whether they are words or numbers, and convert them into fully-searchable digital documents.
Better searchability
Enhanced Information Retrieval
With KlearStack’s automatic data structuring it is now possible to retrieve data using a simple search. KlearStack’s AI supports sorting data into not just predetermined fields such as Invoice number, Supplier name, VAT details, but also custom fields as defined by the user. These fields can also be customized as per your requirements.
Granular Insights
Extraction Up To the Line Item Level
The line item extraction feature lets you create a table that lists all the items on the invoice. For example, if there are 20 items on your invoice, you can find them all listed and organized clearly under the Line Item section of our dashboard. You can create fields like Line item number, description of the item, any code if given, unit value, and more.
Reduced Overheads
Time, Cost and Manpower Efficiencies
Cut not only manpower costs for manual data entry jobs, but also reduce your overheads like printing, copying, QA tools and more. Time spent on manual data entry, auditing that data, or inspecting accuracy levels, can now be directed towards other productive tasks that are of consequence to the success of your business.
