SUPERCHARGED METADATA CATALOG

Ask your metadata
about your data.

At the core of effective data management lies metadata — the key to understanding what you have, where it lives, and why it matters. Diskover transforms massive amounts of unstructured data into living intelligence, enriching datasets with business context that fuels automation, analytics, and AI-powered insight.

Enriched Metadata Catalog

Tagging

It’s the “who, what, where, when, and why” behind every file, dataset, and workflow. As the connective tissue of your digital ecosystem, metadata transforms raw, unstructured data into context-rich assets. By centralizing and enriching metadata, organizations gain the clarity to discover insights faster, automate workflows, and power AI-driven decisions with confidence.

Diskover transforms simple file attributes into a living metadata ecosystem. As data is indexed, context is harvested from filenames, directory structures, and plugin enrichments—creating a searchable, reportable, and actionable metadata catalog.

This living metadata ecosystem gives teams full control to automate policy-driven workflows, prepare AI-ready datasets, and maintain governance across every storage environment.

CORE
METADATA

The core file and system attributes are the foundational building blocks of your catalog (e.g. file name, file type, timestamps, size, owner, location).

ENRICHED
METADATA

Enrich your metadata catalog with business context, enabling highly accurate datasets. Learn more about our harvest plugins →

SUPERCHARGED
METADATA CATALOG

Blend core and contextual attributes to build curated datasets and unlock true data intelligence and automation.

Global Visibility

Search your entire data environment by any metadata attribute to find what you need instantly.

Data Intelligence

Correlate metadata fields to identify data growth patterns, access trends, and file usage, helping define retention, cleanup, and migration strategies.

Data Mobility

Use metadata attributes to automate data tiering, movement, and cleanup policies based on activity level, cost, or business value.

Curation & Orchestration

Use metadata-driven workflows to curate and organize datasets, then orchestrate automated tiering, cleanup, and movement.

Curated Datasets for AI/BI

Combine core and contextual metadata to assemble hig-value, structured datasets that can be directly used for model training amdanalytics.

Tagging adds a flexible classification layer to your metadata catalog. Diskover supports both user-driven tagging and automated tagging policies—allowing assets to be grouped, searched, and managed according to business logic, project workflows, or lifecycle rules.

Together, manual and automated tagging bring structure and consistency—combining user expertise with policy-driven precision.

Manual tagging.
Authorized users can manually tag files to classify and organize data, flag workflow stages, or identify items for review and governance.
Automated tagging.
Automatically apply tags based on rules and metadata attributes to maintain structured, searchable datasets ready for automation and AI workflows.
Diskover's manual and automated tagging overview
Inefficient data navigation and storage utilization.
Limited visibility into aging and temporary/transient data.
Delays, wasted time, and inconsistencies due to manual coordination.
Ability to keep in check 300+ million high-value files.
Indexing Pixit, Facilis, Windows SMB Share, GB Lab accelerated NAS, and soon SpectraLogic.
Analysis, organization, and automation using AutoTags.
Replaced the need for manual commands and system property lookups with instant tag-based searches.
Enabled automated file deletion using tags and retention policies.
Streamlined ongoing data higiene with structured, tag-driven workflows.
Significant time and cost savings. 
Smart data hygiene and storage optimization at scale.
Faster data access, reduced manual tasks, optimized human efficiency and collaboration.
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