InfoDNA Solutions announces the evolution of their Topla platform with a set of capabilities that bring a greater degree of automation and insights to anyone’s document ‘situation’. This includes:
Organizations have documents and content residing on a mix of systems today. From formal content management platforms (which generally contain well managed metadata and place the file into a particular taxonomy and records plan) to network drives (where people just share files with no metadata and only hope to have a folder structure and file name to help identify what the document represents).
During ongoing business needs (i.e. mortgage processing for a bank, procedure and pharmacy approvals and reviews by insurance companies and hospitals, etc) but also under more adhoc needs like privacy searches (i.e. consumer request for CCPA or FOIA requests), legal ediscovery efforts, acquisition due-diligence or a technical migration from old-to-new = the cost and risk are high to maintain the staff and effort.
Insights brings an analysis of every document – visually – and places it into a particular ‘cluster’ to create automated taxonomy mapping and allow millions of documents to be prioritized and identified quickly.
In perspective, Insights was ran against the entire Enron discovery set of information:
- Over 1,000,000 emails
- Over 44,000 attachments with over 350,000 document pages
The completed results were created within five hours with Topla Insights.
Where this is especially powerful – and economically valuable – is in the area of mergers and acquisitions. Topla Insights was utilized by an energy company during the discovery phase of a merger of another organization.
- 21 million documents (100 million images) had to be classified for: retention, security, storage and access
- Content enablement was not an option. Had to work with original images
- 100 million images were reduced to 17,000 objective visual clusters that were prioritized
- A team of SMEs were able to classify the clusters within 30 days
- A new requirement was defined to where seismic data had to be located and automatically redacted – look for a large graphical box with a lot of horizontally oriented wavy lines
- Within the clusters, seismic data was automatically located and redacted
Insights ran against the entire data set in under a week to accomplish the task.
All communication is made up of language – and language given context and form using natural language processing (NLP) technologies. The utilization of computational linguistics to understand the different between ‘Paris Hilton’ the hotel and the person. But in business value, Topla Suzenza utilizes pre-trained NLP to identify the entities, concepts, tone and allow the identification of more ‘toxic language’ in a document or email. Also allows for the flagging of those items that need further review – thus reducing the human time and monetary cost in the act of due diligence or discovery by 80-90%.
InfoDNA Solutions is continuing to build out capabilities within their Topla platform to bring end-to-end automation to document analysis, insights and automations to make the act of one-off needs easy or a larger migration and consolidation possible. All for the least cost, shortest time window and greatest effectiveness. Learn more at www.infodnasolutions.com