Legal Support Platform

IntuView differs from all other E-discovery tools in that it does not use mere "string search" but identifies and disambiguates the exact entity regardless of the language or permutations of the name of the entity or the idea.  IntuView identifies relationships between entities, sentiments, events and other salient information, categorizes and prioritizes the documents and feeds the extracted information into a semantic database and into reports that succinctly summarize the information of the texts.  The user may then query the database for texts that contain any combination of information – even if the user does not know exactly what he or she is looking for.  Reporting and querying functionalities enable the user to search for entities retrospectively after the scan, whereas humans would have to go through all the information again.

 

IntuView performs automated recognition, resolution and aggregation of mention of entities.  Names are recognised and matched regardless of their spelling. There is no need to pre-define a level of ambiguity; IntuView “reads” the name in the text, identifies its source orthography, and matches it with an alternative spelling or nickname. IntuView then populates a database with all entities in the batch of documents and all contextual and implicit information on those entities. Thus, a person’s name that is mentioned in one document will be recognised as matching his name – even if a nickname is used – in another document, all information on that individual in both documents is linked to that entity along with implicit information such as gender, ethnicity, and status derived from the name itself.

 

Similarly, an organisation unknown to the user will be flagged with all persons linked to it and a place will be linked to its “parent” allowing “fuzzy searches”.  This process would usually take many hours of expensive man-hours by various legal and language experts.

 

IntuView Legal E-Discovery Platform analyses all formats of text: MS Word documents, Web pages (HTML); PDF, Plain Text; Excel; Outlook Mail; Calendar and Contacts (PST); PowerPoint and others.

 

  • Other features of the platform include:
    Metadata:

    • Each document receives a unique identification of each document that identifies it and the “batch” from which it originated.

    • Relationship status (parent/child) links Emails and attachments.

    • Document title - name of document/file 

    • Document format. 

    • Document date - from metadata.

    • Document date as extracted by IntuView (the “real” date in the text).

    • Document Author - from metadata.

    • Document Author as extracted by IntuView (the person who seems to have authored the document according to the text).

    • Email – author, recipient, CC and BCC.

    • Other Metadata (size, last opened etc.)

    • Presentation of the text in two formats:  in raw text (.txt) format; the original text.

    • Automatic categories: domains (the “topics” of the document); theatre (the geographical theatre of the document); priority (the degree of relevance - either in general or specifically vis-à-vis that domain); document type (e.g. “letter”, “invoice” etc.); duplicate document.

 

  • Manual tags - a set of manual tags or comments that the reviewer adds and can be used for retrieval and eventual automated categorization, such as free text, or user-defined tags such as relevance, issues, referral to someone on the team for reading or action, etc.

  • Entity extraction including identification of entities (persons, locations, organizations, events, objects, addresses, bank accounts etc.), relations between them, aggregation of information on them from the text, sentiment towards them and co-references of each entity

  • Content Manager for uploading new specific entities and ontologies

  • Search capability according to any of the information extracted.