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Search, Contextualize and Categorize

With Natural language processing, or NLP, machines now has the ability to read and understand text and spoken words in much the same way humans can and even surpass human abilities to read text, contextualize contents, measure sentiment, facilitate search and determine which parts are important. As e-filing and electronic document archiving becomes a reality, removing the manual and the subjective human factor is sure to introduce multiple benefits in terms of reducing sources of error, enhancing productivity and cutting processing time across a wide spectrum of industries.

Semantic AI

WHOsWHO – Name Transliteration & Matching

Matches individuals names against a list of potential name variations across databases

AutoTick – Automatic Document Classification

Upload, OCR and Classify Scanned Documents

Semantico – Semantic Documents Search

Semantic search of document with relevant concepts

Industries & Use Cases

Extract relevant patient data from medical documents

Identify at-risk patients based on medical records contents

Search for clinical cases to identify similar healthcare conditions

Protect sensitive patient health information from being disclosed

Extract disputing parties data from filed cases

Refer cases to the appropriate court or judge based on area of specialization and jurisdiction

Search for closed cases of similar type, article of law or judgement

Protect sensitive personal information from being disclosed

Extract financial and personal data from financial documents

Classify loan applications to help with approval workflows

Search for financial documents by certain narratives

Protect sensitive personal information from being disclosed

Extract health, financial and personal data from financial documents

Categorize medical insurance claims according to symptoms for underwriting

Analyze past fraudulent claims to detect applications with similar characteristics

Improve customer service by routing emaill requests to the right person