Add relevant metadata, keywords and other labels and/or descriptions to improve content findability.
Simplifying complex data classification issues enables more relevant document searches and more efficient content governance.
After understanding and eliminating unnecessary content using powerful ROT (Redundant, Obsolete, Trivial) analysis, valuable data can now be moved to the right place to increase business efficiency, productivity and save resources and storage costs.
Extract information from unstructured data and with ML, NLP and text extraction modules and transform it into structured insights to inform business plans.
Utilise Proventeq’s semantic abilities plus graph technicalities to develop unstructured data into insightful structured information to boost ROI.
Adopt AI, NLP, and ML tactics to help develop operational processes to make informed business decisions.
Review existing content to understand usage patterns and determine high-value content to be migrated during the migration process.
Remove unwanted content and Redundant, Obsolete or Trivial (ROT) data to improve secure content architecture and prevent data breaches.
Instead of paying to store exponentially more data, by removing irrelevant data before migration, you reduce storage needs, cost and management time.
According to Gartner, by 2024, more than 45% of IT spending on infrastructure, software and business...
According to projections from IDC, nearly 80 percent of global data will be unstructured by the year...
Data is growing at an exponential rate for organizations of all sizes. IDC predicts worldwide data c...
Quickly and accurately develop a deeper understanding of your business content with our AI-powered software.
