AI CONNECTOR

Ask in plain language. Approve the next step.

The AI Connector links the AI tool or agent platform you already use to the Diskover metadata catalog. Ask where storage is overspent or which folders have gone cold, get the matching files with a recommended next step, and approve it before Diskover tags the files.

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Diskover AI Connector answering a plain-language question about cold project folders, with matching folders and an approve button

HOW IT WORKS

How the AI Connector works.

The AI Connector reads the catalog, which describes every file across your storage. File contents stay in your storage and out of the conversation.

See it in action: watch this quick demo
How the Diskover AI Connector works in four steps: ask, find, recommend, approve

THE DIFFERENCE

Same question. Two very different days.

The question every storage team gets: “Which old project files can we delete, and who owns them?”

The same storage question answered with four manual steps today and three steps with the Diskover AI Connector

ASK IN PLAIN LANGUAGE

What you can ask.

Questions run against one catalog of every file, across every storage vendor, tier, and location.

Find cold data.

See which folders have gone quiet, how much capacity they hold, and who owns them.
Which project folders have not been modified in 12 months?

Find duplicates.

Locate the largest duplicate files across every storage system at once, and see where each copy lives.
Where are the largest duplicate files across our storage?

See usage by team.

Break storage down by owner, department, project, or tag, so each team sees what it uses.
Show storage used by each department, largest first.

Plan tiering.

Estimate how much capacity a tiering or archive move would free, before any file moves.
How much capacity would we free by archiving files older than 3 years?

Prepare data for AI.

Assemble a candidate training set from catalog attributes and tags, ready for review.
Show storage used by each department, largest first.

Tag for action.

Mark files for cleanup, tiering, or review, with your approval, so your workflows can act on them.
Tag files older than 2 years in the shared drives as archive candidates.

BENEFITS

Why it matters.

Answers for everyone.

Anyone with access asks in plain language, without a ticket to the storage team or a query language to learn.

One view of every file.

Each question covers network-attached storage (NAS), object, and cloud storage in one catalog.

Tags first, then approve.

The AI Connector searches, reports, and tags. Files move only through workflows your team sets up.

Access and audit included.

The same group-based access controls and audit trail as the Diskover interface apply to every AI request.

AI AGENTS

Built for AI tools and agents.

The AI Connector is the Diskover MCP Server. It uses the open Model Context Protocol (MCP) standard, so it works with AI tools such as ChatGPT, Claude, and Microsoft Copilot Studio, and with agent and workflow platforms such as n8n, on desktop or mobile. Every AI tool and agent reads the same catalog, with the same group permissions and the same audit trail. Read why agent-ready data is a different standard from AI-ready data, or see how the team built the connector.

Diskover AI Connector links ChatGPT, Claude, Microsoft Copilot Studio, n8n, and any AI tool or agent that supports MCP to one metadata catalog

FAQ

Questions about the AI Connector.

The Diskover AI Connector is the Diskover MCP Server. It lets AI tools and agents search the Diskover metadata catalog in plain language through the Model Context Protocol (MCP), and it returns matching files with a recommended next step.
Any AI tool or agent platform that supports MCP, including ChatGPT, Claude, Microsoft Copilot Studio, and n8n, on desktop or mobile. Your team keeps the AI tool it already knows.
The AI Connector reads the catalog, meaning file attributes such as name, path, type, size, owner, dates, and tags. File contents stay in your storage and out of the conversation. Like a librarian, the catalog knows every file by its card, without reading every page.
The AI Connector finds files and tags them after a person approves. It does not move or delete files. Moves, archives, and deletions run in the Diskover workflows your team sets up, and those workflows can also require an approval tag before they act on a file.
The AI Connector applies the same group-based access controls as the Diskover interface, so each person and agent sees only the data their group can see, and every request is recorded in the audit trail.

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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