Services
Your archive is a gold mine.
Stop treating it like a landfill.
Most archive migrations move files from one system to another and call it done. The metadata degrades, the editorial context disappears, and years of institutional knowledge arrive in the new world as unsearchable noise.
We do the opposite; your material arrives enriched, structured, and ready to use
as if it was born in the new system.
The Problem
The archive problem
nobody wants to talk about
Every media organization we walk into has the same dirty secret. Somewhere in the building or spread across multiple buildings, cities, and storage tiers sits an archive that nobody trusts.
Journalists know the footage exists. They shot it, they edited it, they aired it. But finding it again is so painful that most people would rather re-shoot, re-download from an agency, or start from scratch than attempt a search.
The archive has become a graveyard instead of a library.
The reasons are always the same. Metadata was stripped or degraded every time a file moved between systems. Editorial context which story a clip belonged to, which journalist selected it, why it was chosen was destroyed the moment it was archived. Search is primitive: no transcription, no face detection, no semantic capability, just filenames and whatever keywords a library team managed to add manually before budget cuts made even that impossible.
And the architecture itself has fossilised. Files sit behind restore queues that take minutes or hours. Storage is fragmented across MAM systems, nearline tiers, tape libraries, and object stores that don't talk to each other. In some organisations, the archive index has grown so heavy that older files simply stop appearing in search results; not because they've been deleted, but because the system gave up trying to show them.
So when the time comes to migrate to move to a new MAM, to consolidate storage, to go cloud-native organisations face a terrible choice. Move everything quickly and accept that most of it will arrive as unsearchable, context-free media blobs. Or try to fix the metadata manually, which would take years and cost
more than the new system itself.
That's the choice most people think they have. It's not.
Your archive isn't broken because the content is bad. It's broken because every system it passed through stripped away the intelligence that made it findable.
$23.5M in annual savings.
178 roles freed up.
One engagement.
Our Approach
Migration as transformation,
not transportation
We don't treat archive migration as a logistics exercise. We treat it as an opportunity to fix decades
of accumulated damage and to make your archive dramatically more valuable than it has ever been,
including the day the footage was first shot.
Our approach has three layers that work simultaneously.
Layer 1
Automated bulk migration for speed
The sheer volume of a broadcast archive makes manual migration impossible. We build automated pipelines that handle the heavy lifting: ingesting from legacy MAM systems, tape libraries, nearline storage, object stores, and whatever fragmented architecture your archive currently lives in. The automation handles format conversion, quality validation, and systematic transfer at scale so migration doesn't take years.
Layer 2
AI-powered metadata enrichment
As content passes through the migration pipeline, we don't just preserve whatever metadata existed. We upgrade it. AI-driven transcription, face detection, object recognition, scene classification, and semantic tagging are applied to every asset. Footage that lived in your old system with nothing but a filename and a date now arrives in the new system with searchable transcripts, identified speakers, recognised locations, and structured editorial metadata.
Layer 3
Human editorial inference
AI can identify a face. It can't tell you why that interview mattered, or that this particular cut was the version approved by the editor-in-chief, or that these three clips were gathered for an investigation that never aired but might be relevant next month. That layer of editorial intelligence requires human inference; and our team, made up of people from journalism and media production, knows how to read the editorial traces that technology alone would miss. We work with your library teams and editorial staff to map the institutional knowledge that exists in people's heads onto the migrated archive.
The result: material arrives in your new system not as a degraded legacy dump, but as content that feels native, properly tagged, fully searchable, editorially contextualised, and immediately useful.
We don't just move your archive. We make it smarter than it ever was.
What Makes This Different
Not a vendor migration. A content transformation
Most archive migrations are run by system integrators or the MAM vendor themselves. They focus
on one thing: getting files from System A to System B. The metadata that doesn't map cleanly gets flattened, simplified, or dropped. The editorial relationships between assets which clips belong together, which sequences were built from which raw material are severed. The archive arrives in the new system technically complete but editorially hollow.
We approach it differently because we understand what journalists actually need from an archive. We've sat in newsrooms and watched reporters abandon their own archive because search was useless. We've seen library teams manually logging thousands of assets because the automated ingest destroyed the metadata. We've mapped workflows where getting a single piece of archive footage to a journalist's timeline required four platform switches, a restore queue, and a colleague's help.
That experience shapes everything about how we design a migration.
We start with the new metadata design, not the old one.
Before we move a single file, we design a purposebuilt, hierarchical metadata schema for the destination system; one that reflects how your organisation actually works and what your journalists actually search for. Then we map the old metadata forward into that new structure, filling gaps with AI and human inference along the way.
We preserve editorial context.
File relationships, story associations, editing decisions, sequence structures, the invisible editorial intelligence that most migrations destroy, we capture and carry forward.
We prioritise by editorial value, not alphabetical order.
Not all archive content is equally urgent. We work with your editorial and library teams to identify what gets migrated first based on reuse frequency, rights windows, upcoming programming needs, and institutional significance.
The Process
How it works
Phase 1
Archive Audit & Index
We create a complete index of every archive component in your current environment: every MAM instance, every tape library, every nearline tier, every object store, every offline backup. We map what's connected, what's orphaned, and what's at risk. This gives you, often for the first time,
a single view of everything you actually own.
Phase 2
Metadata Design & Mapping
We design the metadata schema for the destination system hierarchical, scalable, AI-compatible, and built around how your teams actually search and browse. Then we build the mapping rules that translate old metadata structures into the new schema, identifying where AI enrichment and human inference will fill the gaps.
Phase 3
Priority Planning
Not everything migrates at once. We work with your editorial and library teams to build a phased migration plan based on editorial value, rights sensitivity, reuse frequency, and technical complexity. High-value, high-reuse content moves first. Deep archive follows in structured waves.
Phase 4
Automated Migration & Enrichment
The migration pipeline runs: bulk transfer, format validation, AI metadata enrichment, human editorial review on flagged assets, and systematic ingest into the destination system. Quality checks run continuously. Nothing arrives in the new system without passing validation.
Phase 5
Verification & Handover
We verify the migrated archive against the original index confirming completeness, metadata integrity, and searchability. We train your library and editorial teams on the new metadata structure and search capabilities. And we document everything so the knowledge doesn't leave when we do.
100%
Archive components indexed and mapped before a single file moves.
3 Layers
Automated transfer, AI metadata enrichment, and human editorial inference — working simultaneously.
Born Native
Migrated content arrives searchable, structured, and editorially contextualised — not as a legacy dump.
Standalone or Integrated
Available as an independent service or as part of a full newsroom transformation
Common Achive Problems We Solve
If any of this sounds familiar,
we should talk
When metadata is poor and search is primitive, journalists route around the archive entirely — re-shooting, re-downloading, duplicating work. A properly migrated archive with AI-enriched metadata and modern search transforms the archive from a burden into a competitive advantage.
Every MAM migration puts the archive at risk. Without a deliberate migration strategy, files arrive in the new system stripped of context and unsearchable. We ensure your archive survives the transition intact — and arrives better than it left.
Tape libraries, nearline storage, multiple MAM instances, object stores spread across cities — we've seen it all. Our audit creates a single unified view, and our migration consolidates everything into one searchable, accessible system.
The restore queue is a symptom of fragmented, multi-tier archive architecture. Modern cloud-native systems eliminate the restore step entirely — all content, past and present, is available on equal footing. We design the migration to deliver that outcome.
Manual metadata entry is heroic but unsustainable. AI-powered enrichment during migration means every asset arrives with transcriptions, face detection, object recognition, and semantic tagging — giving your library team a foundation to build on rather than a mountain to climb.
That's more common than you'd think. Our archive audit and indexing phase gives you a complete picture of your holdings for the first time — often revealing content that's been effectively lost for years.
Part of a Full Transformation
Archive migration is one stage of our end-to-end change management methodology. When we're redesigning your entire workflow — from system architecture through metadata design through training and launch — the archive migration is integrated into the deployment phase, ensuring everything arrives in the new world together.
Standalone or Part of a Transformation
One service, two ways to use it
Brief case study preview
A major Middle Eastern broadcaster
Archive rescue during full transformation
Multiple fragmented archive systems, manual archiving procedures consuming entire teams, metadata so poor that journalists bypassed the archive entirely. Our migration consolidated everything into a unified, AI-enriched, searchable system — eliminating the restore step and giving journalists instant access to years of content they'd effectively lost.
A major Australian broadcaster
Consolidating archives across five cities
Archive fragmented across multiple MAM instances, tape libraries, and nearline tiers in Sydney, Melbourne, Adelaide, Brisbane, and Perth. Different cities on different systems, with no unified search. We mapped and indexed every component, designed a unified metadata schema, and built the migration plan to bring it all together.
Related Service
Specialist services
These capabilities are part of every full transformation engagement
but they're also available as standalone services for organizations with specific needs.
Let's get started
Ready to unlock your archive?
Whether you're planning a MAM migration, consolidating fragmented storage, or simply trying to make decades of content findable again, we can help. Every engagement starts with a conversation about what you have, what's not working, and where you want to be.