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Auto Enrich Metadata & Classification

Envision the automatic application of comprehensive metadata to all your information. Centralpoint equips you with tools to manage robust, N-tiered metadata and Taxonomy. This includes scheduling the indexing or ingestion of structured and unstructured data, enabling metadata application based on record content.

Centralpoint facilitates scheduled Data Transfer and Transformation. These tools allow you to traverse diverse databases or file folders, scanning and applying metadata based on predefined rules. Centralpoint Data Cleaner functions as a rule dictionary or repository, guiding Data Transfer processes. This empowers you to scan both structured data (Oracle, IBM, SQL, Json, XML, ODBC) and remarkably unstructured data (PDF, Word, XLS, PPT, CAD, Video) from other systems or file folders.

Centralpoint's Data Transfer (or Transformation) tools eliminate the need for manual data entry or tagging. These tools enable cross-referencing of different taxonomies, connecting disparate information to create a comprehensive Knowledge Management solution—without requiring manual upkeep. This approach also lets you return to simply asking your staff to store files wherever they prefer.

Centralpoint's scheduling feature allows you to regularly scan specified locations, including subfolders, detecting, indexing, scanning, and ingesting new files while applying relevant metadata. Centralpoint's metadata includes MphC, enabling management of multiple hierarchical tiers of Taxonomy (Ontology). This empowers you to handle numerous dictionaries, including the horizontal connections between diverse metadata or Taxonomy types.

When properly configured, Centralpoint's Automated Metadata functions similarly to a personalized Wikipedia, linking everything together, including Role-based Security to ensure users only access what they're authorized to see. 


Schedule a Demo!

Our team will set up a live,
High Fidelity Prototype of your project
to prove our capabilities (including
ingesting some of your sample data) at no cost.