Solution Design Guide

Intelligent
Tape Archive.

A design guide for building archives that capture intelligence before data goes to cold storage - keeping insights accessible for AI, analytics, and compliance, without the egress costs.

Capture intelligence before archive Query without egress Hardware agnostic Works with any storage
Archive & Intelligence
01 / Context

Why intelligent archiving matters.

Traditional archives become black boxes. Data goes in, and the insights stay locked away - unreachable by the models, analysts, and auditors who need them most.

The problem today

  • AI can't see archived data
  • Egress costs block access to insights
  • No visibility into what you actually have
  • Compliance requires expensive recalls
  • Data hoarded on costly primary storage

The opportunity

  • Capture intelligence before archive
  • Query insights without moving data
  • Complete transparency into cold storage
  • AI and compliance workflows enabled
  • Archive faster and reduce storage costs
The goalAn archive where intelligence stays accessible - even after the files themselves go cold.
02 / Principles

Four principles for AI-ready archives.

These turn tape from a black hole into active AI infrastructure - without the traditional tradeoffs between cost, access, and intelligence.

01 / Capture

Capture intelligence first.

Extract metadata, structure, context, and relationships before files move to archive. The intelligence layer must persist independently of file location.

02 / Separate

Separate intelligence from storage.

Files rest in cold storage. Intelligence stays hot and queryable. AI and analytics access insights without ever touching archived files.

03 / Query

Query without egress.

90 %+ of queries are answered from the intelligence layer. Only retrieve files when they are actually needed - never just to discover what you have.

04 / Agnostic

Hardware agnostic by default.

Works with any tape library, any disk cache, any S3-compatible storage. No vendor lock-in. Each layer scales independently.

03 / Architecture Pattern

Intelligence layer + deep archive.

Three concerns, cleanly separated. Active storage stays fast. The intelligence layer stays queryable. The deep archive stays cheap.

Stage 01 / Source

Source Storage

Disk, NAS, Object Storage - wherever files live today. No migration required.

NASDiskS3
Extract
Stage 02 / Intelligence

Intelligence Layer

Metadata, structure, context, relationships. Queryable forever - across all storage.

SearchAIAudit
Archive
Stage 03 / Archive

Deep Archive

S3-compatible tape storage. Files at rest, at the lowest possible cost per TB.

TapeS3Cold
Key insight.  Files become passive artifacts in the deep archive. The intelligence layer becomes the active working surface for AI, analytics, search, and compliance.
03a / The Two Layers

MetadataHub + XtreemStore.

The intelligence layer and the deep archive layer - purpose-built, independently scalable, and designed to work together.

MetadataHub

The Intelligence
Layer.

Always-hot proxy for files.

  • Extracts context, insights, and deep metadata
  • Persists a queryable index across all storage
  • Acts as the always-hot proxy for files
  • Answers "What's in my files and on tape?"
We make data findable.
+
XtreemStore

The Deep
Archive Layer.

Files at rest on tape.

  • S3-compatible tape object storage
  • Scalable, low-cost cold tier
  • Files at rest on tape
  • Hardware agnostic, no vendor lock-in
Infinitely scalable & affordable.
Together,
tape becomes an
active AI tier.
Tape stores the data. MetadataHub stores the intelligence. XtreemStore makes the archive infinitely scalable and affordable. The intelligence layer stays hot while files stay cold - active workflows, cold-storage economics.
03b / Working Together

How MdH + XtreemStore work together.

A single flow, four stages. Intelligence is captured once, then queried forever - while files move automatically to the cheapest tier.

01

Source Storage

NAS, S3, Disk - wherever files live today. No migration required.

Starting point
02

MetadataHub harvests & indexes intelligence - once.

Rich metadata, structure, relationships, and context captured at ingest. Build once. Query forever.

Intelligence layer
03

Policy-driven tiering

Automatic tiering and migration via your data-mover of choice. Files move from source to XtreemStore based on policy - no manual handoff, no lost context.

Data-mover partnersPanzura SymphonyStarfishMediaflux
Automatic
04

Deep Archive on XtreemStore

Files at rest on tape. Intelligence stays always-online via MetadataHub - queryable without recall.

Cold tier
Result
90%+ of AI, analytics, and compliance queries answered from the intelligence layer. Files stay cold until truly needed - zero egress for discovery.
04 / Outcomes

What this enables.

The same intelligence layer unlocks three workloads that traditional archives simply cannot support.

AI workflows

Feed models directly from the intelligence layer - no file recalls required for discovery or context.

Compliance

Answer audits from metadata and context. Retrieve files only when they are truly required by the regulator.

Cost reduction

Archive aggressively with full visibility. Most operations never touch the cold tier - so they never pay the egress bill.

90%+
Queries answered without egress
1 / 1000
Metadata proxy size vs. original
$0
Egress cost for intelligence queries
05 / Implementation

Implementation considerations.

Four concerns to resolve when mapping these principles onto real infrastructure.

I.Intelligence Extraction
  • Extract rich embedded metadata, structure, relationships and context
  • Index once at ingest or at first access time
  • Build once, query forever
  • Schema-on-read for evolving attribute sets
II.Storage Architecture
  • S3-compatible interface for the deep archive tier
  • Scale intelligence and archive layers independently
  • Files written to S3 - tape or cloud, your choice
  • Intelligence remains always accessible
III.Data Organization
  • Group related files for efficient batch retrieval
  • Tag-based routing to containers
  • Containers span multiple tapes - no single-tape size limits
  • Retention and legal holds at the container level
IV.Query & Access
  • Global search across all archived data
  • Filter by any captured attribute
  • Retrieve only what you actually need
  • Feed AI and analytics directly from the intelligence layer
06 / Best Practices

Four habits that make this work.

The teams that succeed with this architecture do these four things consistently, from the first ingest onward.

Before you archive

Extract before archive.

Capture intelligence while data is still in active storage, or at access time. Once files are in deep archive, extraction requires a recall - so do it once, do it early.

At ingest

Index everything.

Embedded metadata, file relationships, content structure. The more you capture in the intelligence layer, the more questions you can answer without ever touching the archive.

Architecture

Design for scale.

Plan for billions of objects across distributed environments. The intelligence and deep-archive layers must scale independently and linearly - no shared bottleneck.

In production

Validate continuously.

Cross-reference the intelligence layer against the deep archive. Confirm what you think you have actually matches what is stored - without triggering full recalls.

07 / Summary

Key takeaways.

Building archives that serve AI and compliance workflows, at cold-storage cost.

01

Intelligence first.

Capture metadata, structure, and context before archive. The intelligence layer is the working layer - not the files.

02

Zero-egress queries.

90 %+ of queries answered without ever touching archived files. Only retrieve what you actually need.

03

Complete transparency.

Know what you have. Know where it is. Feed AI and compliance from the intelligence layer, not the archive.

04

Hardware agnostic.

Works with any storage infrastructure. Any tape library. Any disk cache. No vendor lock-in.

Archive becomes - infrastructure, not a graveyard.
Learn more

Ready to design your
intelligent archive?

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Contact

Tell us about your archive.

Short note, real reply. We design intelligent archive deployments end to end - data-mover integration, MetadataHub policy, XtreemStore sizing.