Artificial Intelligence (AI) is a powerful tool for any business or organization to deploy for making the business processes seamless and productive. It accelerates the productivity of human effort by integrating Machine Learning (ML), automation & even Natural Language Processing (NLP). However, what about documentation? When it comes to enhancing the document processing, we can combine the document processing with ai to scan documents efficiently.

Subsequently, actionable & contextual insights can be drawn from the analytical results. Whether interpreting legal documents or driving data-based approvals or financial transactions, AI-based document processing remains a versatile universal option. Over here, we explore some of the best AI document-processing platforms. Hope you enjoy perusing this as much as we have done compiling it!

AI for document processing

1) Xtracta

Xtracta is an AI document processing solution driving the automation software for efficient data extraction from the documents. It serves major brands such as Volvo, where their eDocs platform is deployed to reduce time consumption by two-fifths during invoice input. This processes above 10 million pages monthly via AI engines, devoid of manual templates. This is contrary to conventional optical character recognition (OCR) technology.

What is innovative about this is that the AI engine operates using a continually adaptive deep self-learning algorithm via ML to capture new document layouts without new templates.

2) Serimag

Serimag functions in tandem with the Barcelona Supercomputing Center (BSC), categorizing documents as per neural networks. Its USP is the ingenuity to combine and integrate graphics & text within documents – all independent of parametric coupling modules.

An automatic categorization cum extraction system was conceptualized to automate customers’ supporting documentation processing while standardizing criteria. Consequently, error rates were reduced & promoted versatile document control systems. Furthermore, brand approval cycles also became quicker.

3) ABBYY FlexiCapture

This platform sets an unparalleled precedent by leveraging ML to automate the categorization, extraction & validation of direct business-critical data. This caters to all, be it external customer correspondence or internal operational processes, including invoices/orders, supplementary documentation, taxation, onboarding, or even claims.

Its categorization technology senses all incoming document types, which spans visuals via deep learning & Convolutional Neural Networks (CNN). This sorts documents by their appearance or pattern and classifies text as per statistical cum semantic text analysis. Consequently, documents can be classified as financial, contractual, and so on with differing variants. These can then be auto-sorted.

4) Parascript

Parascript drives computer vision tools, catering for both visual and written classification. Deploying stellar AI techniques, their services are offered to coveted brands, including JP Morgan Chase, Lockheed Martin & Siemens. They deploy an aerial view for character recognition via neural network-powered curve tracing. Computer vision drives activities such as OCR & even handwriting recognition. These include:

– Location or regional address details on correspondence or packages (logistical navigation)

– Auto geolocation sensing using envelope visualization

– Inventory & signature verification

Parascript applies convolutional neural networks deep learning with concealed Markov Models, Bayesian-based algorithms &  support vector machines.

5) Microblink

Microblink is an R&D institution developing computer vision technology optimized for live mobile device processing. Advanced neural networks plus deep learning methods furnish very accurate text recognition, available locally on a mobile device. Features include:

– Live image processing

– Operates offline, locally on-device

– Is compatible with hard & soft copy invoice slips with various global formats

What does the future hold for AI-based document processing platforms?

Well, given the broad scope of AI & its respective applications, this has endless potential. Whether it is data analysis, capture, processing, or insights, AI document processing tools will continue to evolve with time but also be implemented & integrated into existing legacy systems. Not only this but also the fact that data informatics is now becoming an integral part of essential operations. This is commonplace across the board & hence it is vital to ensure that any insights can be derived from specialist sources. With data extraction tools, relevant information & insights can be extracted, analyzed & then extrapolated for further future trend interpretation.


In summary, AI-based document processing will continue to drive data insights as expected growth in the digital economy & field occurs. Whether education, financial services, retail, or transportation – document processing is here to not only stay but flourish with the ever-growing demand for responsive data flow. With this, organizations can drive their throughput even further with efficient processing, faster turnaround times & multitasking at its best for proper, ultimate performance.

This can be further enhanced with the automation of this data implementation for even quicker data extraction. Finally, data-driven insights will set the stage for another revolutionary phenomenon: live data input analysis, wherein information can be interpreted as it is being entered into a system. Therefore, it can be inferred that organizations will certainly benefit by applying an AI-based document process platform like XtractEdge.