Preventing Costly Litigation

The overall average cost per commercial tort case is approximately $400,000…that’s per case.  

TextualETL™ provides an “early warning system” of potential exposure to litigation, complaints, and claims from inside and outside an organization.  Capable of analyzing unstructured “big data” from all inbound channels, including repetitive and non-repetitive data, the risks can be classified automatically according to any number of classifications and categories.  The big data sources include, but are not limited to: emails, social media, employee surveys, contracts, maintenance records, safety reports, blogs, and more. In the context of product liability cases, the system could translate to fewer lawsuits, and, by inference, potentially fewer “catastrophic risk” events such as injury and death.  The TextualETL™ Litigation Early Warning System (LEWS™) offers the prospect of a big risk reduction plus a big cost reduction, and that’s a powerful combination. 


The first major challenge facing any corporation is to deal with the volumes of data that must be processed.  There are many facets to dealing with large volumes of data.  But the most important facet to dealing with large volumes of data is the challenge of “Big Data.”  There are a multitude of sources for Big Data as a corporation can store and process virtually unlimited amounts of data. TextualETL enables focus on the most challenging sources of Big Data, namely the non-repetitive unstructured data found in every company. The platform can be configured to automate the processing of massive amounts of unstructured data in a highly scalable environment.

email icon E-mail.

Process emails from internal and external sources including employees, customers, agents, contractors, and clients.   TextualETL can process the unstructured text of emails and identify fields such as sender, the intended recipient, the date, and the subject of the e-mail, and a host of metadata as identified and characterized as relevant and contextual to your business or organization.

Call Center  Call Center Data

Process voice records and data quickly and easily to uncover potential issues or customer complaints.  Voice Recognition Software (VRS) has made significant improvements in recent years to yield more accurate data and provide real business value in the results. TextualETL integrates with the output from any VRS in .txt format and provides a ready-made dashboard for analysis.

Survey_1 Compliance, Warranty Claims, and Safety Information

Process the feedback and comments on product malfunctions, or perceived malfunctions from customer generated a warranty claims or employee/contractor safety reports. TextualETL can process the unstructured textual information found on the warranty claim that may reflect a complaint.  Process textual content from compliance reports for such areas as FCPA, HIPPA, SEC regs, Dodd-Frank, Consumer Safety, SAR Baines Oxley, and others. Reduce accidents and liability issues by analyzing records and anticipating these incidents quickly and at low cost.

Social Media Vector Online Corporate Reputation

Source a wide range of online and internet content to assess and determine the impact of multiple aspects and dimensions of your corporate reputation including blogs, tweets, posts, feeds, and more.  Any and all textual data can be converted and analyzed for potential non-compliance, risk exposure, and liability.

CollectionMining Customer Interactions

Convert the verbatim feedback and comments of your customer touch-points and interactions via telephone, online feedback, or email into a structured database in order to generate reports, detect correlations, and analyze trends (native or 3rd party tool) for potential exposure and liability.

Customer ProfileCustomer Profiles

Achieve a 360-degree profile of your clients, incorporating demographic information, behavior and attitudes, from their online conversations and interactions with the company.


Survey and Comments Analysis

Process text-based, open-ended answers to the “Comments” section of your survey with an unlimited field size and fast turnaround time for collection and analysis.

Who can benefit?Big_Data_Sources

TextualETL can enable the General Counsel and corporate legal department gain new insights regarding operational and statutory liability and risk exposure and mitigation in a variety of industries and markets.  Here are just a few examples:

Corporate clients

Industries with a large number of employees, customers, partners, contractors and/or users such as banking, finance, insurance, communications, manufacturing and utilities, TextualETL™ enables the collection and analysis of critical information for deployment of a Litigation Early Warning System to prevent costly litigation and the associated catastrophic risks .

Advantages of TextualETL

TextualETL™ provides the ideal platform for a LEWS™ solution. Here are some of the key features:

Advanced Risk Analysis

Including object-oriented indexing and analysis of metadata terms selected and produced by the system.  Customize the system for your specific industry, sector, or customer environment.

Fully Optimized

The TextualETL user-interface is highly functional and optimized for use by trained users of the system.  Use our default library of taxonomies and ontologies for industry specific terms and indexes for a quick setup of corporate risk and liability exposure.


Add your own taxonomy terms and definitions from your own dictionaries, classification models and sentiment vocabularies according to your specific needs.

Textual Disambiguation of terms and entities

Our proprietary approach to textual disambiguation eliminates the confusion of names of companies, products, brands, people by building and creating specific contextual relationship of legal and risk terms.  Never again confuse the “Washington Generals” with the military kind found in D.C. δ

Consistency and Homogeneity

Apply the same analysis criteria to all content sources and avoid any inconsistency or divergence that may arise from processing risk, compliance, and safety data from a wide array of sources and a vast multitude of users and constituents.

Ready for Twitter and all other Social Feeds

Designed to understand both the formal language of the news, all social media, including Twitter’s informal and abbreviated one, in several languages.

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