Intelligent Document Processing

Cognitive Machine Reading: All You Need To Know

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Cognitive Machine Reading: All You Need To Know

When it comes to capturing all data types, especially unstructured, for end-to-end process automation initiatives, companies employ OCR, the technology that has its own limitations.

Companies struggle to extract relevant information, which provides them erroneous reports, data loss, and paperwork overload. In such situations, companies cannot rely only on OCR, and this is where CMR becomes a potential disruptor.

CMR can automate data extraction from structured and unstructured documents that may contain:- 

  • Checkboxes
  • Tables
  • Images
  • Signatures
  • Handwriting
  • Cursive, and more. 

What does CMR stand for?

CMR stands for Cognitive Machine Reading and enables you to surmount the deterrents of digitizing unstructured data and extracting information from credentials.

CMR is developed using proprietary pattern-matching via methods based on content-based object retrieval, which renders significant levels of precision. It detects patterns and associated confidence scores rather than font sets, which helps avoid anomalies. 

Benefits of implementing CMR 

Here are some potential benefits of implementing CMR in your system:-

1. Machine Vision Capability

CMR is the only data ingestion engine that satisfies the complex Machine Vision requirements of extremely unstructured and disparate data, and caters to most document formats.

2. Complex Pattern Identification

CMR provides state-of-the-art Natural Language-based classification with modest data sets, identifying complex patterns in data. CMR extracts information from unstructured data that is complicated to analyze and summarize.

It also analyzes data that cannot be processed with rules, has a minimal or no structure or metadata, and includes non-text-based materials.

3. Seamless configuration

Owing to its streamlined configuration, CMR can get implemented expeditiously as its engine is capable enough to grasp from a limited representative set of documents. You can synthesize massive amounts of customer data via Natural Language Modelling (NLM) to create deeper insights.

4. A Dynamic Alternative to OCR

OCR (Optical Character Recognition) has its limitation in reading unstructured data. Powered by fractal science, CMR is competent enough to read all data types and maintain data certainty and accuracy.

Extract Insights from Unstructured Data

Improve accuracy and speed in handling unstructured documents with AI.

How CMR benefits your business

While CMR portrays extreme competency in capturing all data types, here are specific means through which it benefits your enterprise -

1. Automation Scope Expansion

CMR lets you leverage 85% of the untapped and unstructured data prevalent in your organization, implying that you receive enhanced results by automating deeper processes as well as more complex data.

2. Greater accuracy with data certainty

CMR offers a better capture rate with over 80% accuracy of consistently capturing information. CMR lets you promote the level of data certainty to attain a higher percentage of straight-through processing.

3. Swift ROI

Streamlined configuration and faster implementation by employing smaller data sets for training, CMR boosts automation with efficiency and speed. CMR also keeps learning from your processes and promotes ongoing optimization.

4. Miscellaneous Perks

CMR’s approach to automation provides enterprises with competitive leverage because it -

  • Ingests and processes all types of data, comprising structured data as fixed field text and unstructured data types that include emails, videos, images, and handwritten text.
  • Does not require new templates to be generated each time it must ingest and process new data, unlike OCR. CMR does not rely on template creations and can digitize data regardless of its variance or format.
  • Decodes and processes special characters in several languages via pattern recognition. OCR fails to find the significance behind data in different languages without human interference in the form of labeling or manually reviewing the content.
  • Helps users to scan, filter, and spot precise information required within a document, provided the parameters for the information required are set. OCR cannot localize and contextualize peculiarities in the provided data.

The superiority of CMR to OCR

The perks of employing Cognitive Automation Reading extend to cognitive scanning of information as intelligent engines consistently keep learning from a representative set of documents through Machine Learning. These engines share the acquired knowledge in one process with another.

CMR and Machine Learning transcend way beyond traditional OCR, which, despite being widely employed from a legacy perspective, processes only structured data.

Independent of zones, formats, templates, modes and languages, CMR processes, curates, and categorizes data across several languages, establishing that it stays available for downstream policy processing.

You can also export data for downstream consumption across several formats such as CSV, XML, JSON, and DB schema.

CMR resolves the challenge of processing unstructured data that haunts various industries that deal with data capturing each day. CMR is particularly beneficial for legacy systems of records and copious documents and data stored in multiple formats.

Final Words

CMR expands your automation scope and provides a better ROI, enhanced data certainty, and constant improvement for optimizing the automation of business processes.

CMR offers substantial benefits over OCR, considering its ability to process structured and unstructured data without missing the intricacies. 

Companies with data extraction in their list of mundane activities must consider switching to CMR to gain better insights into data, extract more information, enjoy a better ROI, and process almost all data types.

Suggested Case Study
Automating Portfolio Management for Westland Real Estate Group
The portfolio includes 14,000 units across all divisions across Los Angeles County, Orange County, and Inland Empire.
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Pankaj Tripathi
Written by
Pankaj Tripathi

Helping enterprises capture data for analytics and decisioning

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