Top 5 AI-Document Processing Platforms For Your Business

Introduction:

Avenues and applications that AI opens up have no bounds. Today machine learning algorithms are capable of solving human-like tasks involving sound and vision. Computer vision techniques today are going beyond images themselves to any digital information. With this unprecedented amount of computing power, artificial intelligence can now afford to compute and learn in real-time. Primarily machine learning is used for predictive analytics, document classification, and decision support for online transactions in  AI document processing technology.

Intelligent Document Processing – Phases:

Phase 1: Preparation and Classification

Phase 2: Extraction and Formatting

Phase 3: Input to Downstream Applications

Categories of IDP Vendors to navigate the landscape:

·        Innovative IDP vendors

·        Legacy IDP vendors

·        Niche IDP vendors

·        Systems Integrators with IDP offerings

·        Technology providers with IDP components

Here, each vendor views the IDP challenge through a different lens and, therefore, has developed various solutions

These applications can help document processing tools to find their niche:

·   An actual valuation of real estate portfolios

·   Support documentation for easy approval of loans

·   Invoices for further references

·   Online verification and identification of documents

·   Clause detection in various and multiple legal documents

Today automating document processing comes with plenty of benefits like automatic inspection, organizing information, event detection and navigation.

Platforms that provide top document processing AI-based services are as follows:

1.     Xtracta:

The leader in the market is Xtracta. It provides automation software fueled by document processing and artificial intelligence. By providing its services to big brands like Volvo, where the eDocs is helped to cut down on time by almost 40% consumed in invoice entry. Xtracta powered services are known to process over 10 million pages per month. It does wonders with the help of an AI document processing that requires no manual templates, unlike the widespread traditional optical character recognition(OCR) methods. Here the AI engine is a “set and forgets” machine as it self-learns new document designs without the need for further new templates.

2.   Serimag:

Serimag works parallel with the famous Barcelona Supercomputing Center (BSC) to classify co-plicated documents based on neural networks. Serimag is unique because of its innovation to merge both text and graphics in a paper in an integrated manner. And this is carried out without the need for any further parametric coupling modules. To automate the processing of customers supporting documentation and standardize the criteria, an automatic classification and extraction system was eventually developed by Serimag. This resulted in the reduction of errors and more robust document control systems. Automatically the company approval cycle has been further reduced by hours for smooth processing.

3.     ABBYY FlexiCulture:

Extracting, validating, direct business-critical data from incoming customer communications and operational processes, like supporting documents, invoices, onboarding documents correspondence, tax forms, claims, or orders everything is quickly done. This platform raises the bar by leveraging machine learning in a way to classify automatically. Classification technology now detects every incoming document type, including images, using deep learning platforms, Convolutional Neural Networks(CNN), and sorts documents by pattern or appearance. Text classification relies on semantic text analysis and statistics. And, this further helps in classifying documents into different types like a bank statement, tax form, contract, invoice, and variation to automatically sort them in a specific pattern.

4.     Parascript:

Parascript is known to provide computer vision solutions for both text classification and image. They furthermore deploy state-of-the-art artificial intelligence techniques to achieve this. This U.S-based organization offers its services to Lockheed Martin, JP Morgan Chase, and Siemens. They use a topological approach for character recognition using a curve tracker powered by neural networks. Parascript also uses computer vision to perform crucial tasks like handwriting recognition and optical character recognition.

Computer vision solutions provided by Parascript are as follows:

  • The region of interest is located on parcels, flats, and letters.
  • Automatic location detection option on envelope images makes it easy
  • It also checks the signature and stock verification

Parascript also uses convolutional neural networks for Hidden Markov Models, deeplearning, Bayesian-based algorithms, and support vector machines.

5. Microblink:

This is an R&D company that develops computer vision technology optimized for real-time processing on mobile devices. Deep learning and advanced neural networks techniques provide the most accurate text recognition locally on every mobile device.

  • The real-time image processing platform
  • Works on-device offline, without an active internet connection
  • Supports electronic and paper payment slips in various countries and standards

Intelligent Document Processing Software Makes Processes Effective:

1. Banking and Insurance

2. Healthcare

3. Human Resources.

4. Government

5. Legal

Conclusion:

The future is AI document processing intelligent; with more and more organizations embracing this new technology in their processes on a much larger global scale, we can say it is the ultimate future for all industries. Irrespective of the size, like big or small, one can utilize the features of IDP in delivering the best services and products. IDP is known for digitizing and securing data, but it is also known to save operation costs and valuable time. IDP further reduces errors related to manual data entry; thus, it increases productivity where employees can be further used in other significant tasks like generating revenue and improving customer experience. The adoption of IDP has also proven to help companies and businesses to reduce data extraction inaccuracies and promote growth.

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