ENRICHED METADATA CATALOG

One catalog, every file, with the who, what, and why attached.

Diskover indexes every file across every storage vendor, tier, and location into one metadata catalog, then adds the context your business runs on: project, owner, status, and lineage. Search, policies, the AI Connector, and AI/BI pipelines all work from the same catalog, while the data stays in place.

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A Diskover metadata catalog record for a media file, with core, enriched, and tag layers and the source of each field

WHAT IT IS

What a metadata catalog is.

A metadata catalog is a searchable index of information about your files: what each file is, where it lives, who owns it, and when it was last used. It holds the description of every file, not a copy of it.

Most organizations cannot see that far. Thales reports that only 34% of organizations know where all their data is. Diskover builds one catalog for file and object data across every storage vendor, tier, and location, so every team searches the same place.

34%

of organizations know where all their data is.

Thales, 2026 Data Threat Report

Like a librarian, the catalog knows every file by its card, without reading every page.

HOW A RECORD GROWS

Three layers of context on every file.

The more Diskover knows about a file, the more precise the search and the action.

1

FROM STORAGE
Core metadata

FROM: the storage system at every scan.
FIELDS: name, path, size, type, owner, group, permissions, dates.
2

BUSINESS CONTEXT
Enriched metadata

FROM: plugins, folder structure, file headers, and your business systems.
FIELDS: project, department, client, workflow stage, cost, media details, genomics info.
3

DECISIONS
Tags

FROM: people, rules, and the AI Connector, with your approval.
FIELDS: approved, archive candidate, legal hold, retention class, delete candidate, ai-ready.

WHERE THE CONTEXT COMES FROM

Your workflows already describe your files.

The context your teams need is already there, in names, folders, file headers, and business systems. Diskover harvests it into searchable fields with several metadata enrichment plugins.

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File and folder names

Project codes, client names, versions, and dates are already written into names. Path Tokens splits them into searchable words.

ClientABC/ProjectPhoenix_Final_2024-01-15
Becomes →
client • abc • project • phoenix • final • 2024-01-15

Folder structure

Folder names show the workflow stage, and File Kind sorts file types into the categories your teams already use every day.

/incoming → /QC → /delivered

Breadcrumb

A small key-value file in a project folder adds its owner, project, department, and cost center to that folder’s record.

project: AlphaResearch
cost_center: CC-4521

File headers

IImage, media, PDF, OpenEXR, and BAM plugins read the metadata embedded in file headers, so teams can search by camera, codec, or author without opening a single file.

camera settings • codec • resolution • author • sample ID • bam info

Business systems

Data from your asset, order, and production systems joins the file record, including CSV exports, Xytech Media, Autodesk Flow Production Tracking, and Avid.

case ID • order status • shot status

Storage systems

Storage details sit next to the file metadata: Dell PowerScale SmartPools, Dell quotas, Dell Unity, and Windows and Unix ownership and permissions.

tier • quota • owner • open permissions

TAGGING

Tags turn context into decisions.

A tag records a decision about a file, so every team and every workflow reads the same answer. Tags come from three places, and they stay with the file.

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Tagging in the Diskover metadata catalog: people, rules, and the AI Connector add tags, and workflows act on approved tags

Tags drive workflows.

Policies tier, archive, move, or delete the files that carry the right tags, on a schedule, with a record of every action.
Explore curation and orchestration

WHAT IT POWERS

One catalog behind every Diskover capability.

Every capability reads and writes the same catalog, so a tag added in one place is visible everywhere.

Global visibility.

Search every storage system at once, by name, owner, age, project, or tag.
Explore

Data intelligence.

See capacity, age, cost, and growth by team, project, or storage system.
Explore

Data mobility.

Tier and archive files by usage and value, and keep them searchable after they move.
Explore
One metadata catalog image

Orchestration.

Run policies on tagged files, on a schedule, with a record of every action.
Explore

AI and BI pipelines.

Curate datasets by any attribute and deliver them with their context.
Explore

AI Connector.

Ask the catalog a question in plain language, and approve the next step.
Explore

1.4B

files indexed in 2 hours, on 3 nodes

29

metadata enrichment plugins

435+

platform features

LINEAGE

Your data’s story matters more than its zip code.

Where a file sits is only the start. Support governance efforts with traceable lineage that helps teams answer audits, retention questions, and policy reviews faster.

Where it came from. The catalog records when Diskover first saw each file, and the folder and project it belongs to.
How it moved. Files stay in the catalog after they move between network-attached storage (NAS), object, cloud, and archive.
What changed. Index Differential compares two scans and lists every file that was added, removed, or changed, for migration checks and change tracking.
Who owns it. Owner, group, and department sit on every record, including files whose owner has left.
Explore our AI Connector
File lineage in the Diskover metadata catalog: one file followed from first index on NAS to object storage, with its tags

How tagging enriches your catalog.

USE CASE

Media giant searches 300 million files from one place.

A global media company indexed more than 300 million files across 4 storage platforms into one searchable catalog. Eleven users across engineering, media operations, and finance now find files in minutes instead of hours, and Auto Tag rules drive the retention policies that keep storage lean.

Explore our AI Connector

300M+

files in one catalog

4

storage platforms in one catalog

Minutes

for lookups that used to take hours

AI AGENTS

Agent-ready data starts with a metadata catalog.

AI agents choose their own files while they work. They read the catalog record before they open a file, so the catalog decides what an agent finds, uses, and leaves out.

Read about agent-ready data

FAQ

Questions about the metadata catalog.

A metadata catalog is a searchable index of information about your files, such as name, location, owner, dates, and the business context your teams add. Diskover builds one catalog for every file across every storage vendor, tier, and location. See the full definition in the metadata and cataloging glossary.
A data catalog usually describes tables in databases and warehouses. A metadata catalog for unstructured data describes files and objects. Diskover can send its file metadata to Snowflake and lakehouses, so teams can query both kinds of data together.
The catalog stores the description of each file, not the file. Your data stays in place while the catalog is built, and it moves only when a workflow calls for it.
Metadata enrichment adds business context to the core metadata from storage, such as project, client, department, workflow stage, and cost. Diskover adds it from file and folder names, breadcrumb files, file headers, and your business systems.
Diskover builds the catalog from metadata, not from full-text content. Some enrichment plugins read the metadata embedded in file headers, such as camera settings in an image or the codec of a video.
Indexing runs on the schedule your team sets. After the first full scan, cached scanning reads only what changed, so frequent refreshes stay practical on very large estates.

See it on your own data.

We’ll index a sample of your environment and show you what’s recoverable against your current storage spend.

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