Media & Entertainment Data Management
Cut unstructured media storage costs. Enrich metadata to monetize content. Prepare post-production data for AI pipelines.
Why Komprise for Media Companies?
$1M
SAVED Per PB/YEAR
90%
Faster media asset reuse
ZERO
PII, IP Surprises
The Komprise Difference for Media & Entertainment
Media and entertainment companies store libraries of massive video assets that must remain instantly accessible for reuse, licensing, and AI-driven content discovery. Accurate metadata drives revenues and poor data classification means content goes unmonetized. Komprise delivers visibility into unstructured data with precise data labeling so media libraries are searchable and ready for AI.
Visibility
Sensitive Data
Tiering Cost Savings
Tiering Policies
Media Image Metadata
Customizable Policies
Cost of Storage Refresh
Compliance Reporting
AI Metadata
AI Ingestion
Analytics & Lakehouses
Focus
Storage-Vendor Data Management
Siloed, storage specific
Limited to no support
Limited, only on storage
Limited, Cluster-Based
None
Limited
Lock-in. Costly Rehydration when Switching Vendors
None
None
Manual
None
Storage
Komprise Intelligent Data Management
Global Analytics Across all Storage and Clouds
Built-in sensitive data detection and handling
Save 70% on storage, backup, DR costs
Flexible per Research Group or Department
Extract image metadata (eg EXIF), media metadata (eg codec, resolution) and more with customizable KAPPA
Showback by Media Project with Tiering Policies for each Group’s Unique Needs
No Rehydration Penalty or Data Lock-In
Built-in Chain-of-Custody Reports, Auditing
Serverless KAPPA metadata extraction for PDF, TIFF, EXIF, VXF, Multimedia
Intelligent Caching Keeps Data Secure in Place while Enabling use of AI. Boosts AI ROI by +80%
Iceberg tables for use in Snowflake, Databricks, et al
Data Management in Regulated Industries
Automate & Classify AI Data Workflows
Production Studios
Media libraries sprawl across petabytes of NAS storage, mostly uncurated for AI.
- Discover and classify raw footage, proxies, VFX renders with a unified Global Metadatabase.
- Filter noise (duplicates, outdated renders) to improve AI model accuracy.
- Automate secure ingestion of production footage into AI pipelines with full audit trails.
Broadcasters
Live and archived content must be searchable, licensable, and AI-ready.
- Enrich media metadata with industry and project keywords.
- Detect and exclude sensitive or rights-restricted content before AI ingestion.
- Tier cold archive content to low-cost storage while keeping it instantly accessible.
Music & Publishing
Catalogs contain decades of recordings, scores, and rights documents that need context & structure.
- Search and curate content across file and object silos using rich metadata filters.
- Tag assets with custom metadata (genre, era, rights status) for AI recommendation and licensing workflows.
- Prevent IP and sensitive contract data from leaking into AI training sets.
Reclaim Primary Storage Capacity
Reduce the financial burden of large media files that must be retained and instantly available for future reuse.
- Analyze petabyte-scale files across hybrid storage to understand usage and model costs.
- Transparently tier cold files with custom policies to reclaim 70%+ flash capacity and avoid costly rehydration.
- Discover and confine orphaned and dead data for deletion and storage savings.
Ease Data Mobility
Eliminate the complexity of moving petabyte-scale media assets between cloud, edge and on-premises storage.
- Migrate data 27x faster to new storage without the typical delays, disruptions and data loss.
- Avoid the access and mobility issues of tape and storage vendor tiering with the Komprise no lock-in architecture.
- Get analysis of network and environment to avoid problems.
Automate Metadata Enrichment & AI Workflows
Deliver granular search, metadata tagging and rapid ingestion for content monetization across siloed data estates.
- Understand and filter data by metadata insights with a Global Metadatabase.
- Custom metadata extraction for VXF, TIFF, MP4 etc with Komprise AI Preparation & Process Automation (KAPPA).
- Accelerate AI data ingestion with curated, policy-driven data workflows and 2X faster data transfer speeds.
Dig Deeper
Blog
KAPPA: A Serverless Approach to Metadata Enrichment and Unstructured Data Management
Enterprise AI has entered a new phase in 2026, where plans are executing into production and with mixed results.
Webpage
Global Metadatabase Service
Search across NAS and cloud with a Global Metadatabase Service that scales with your data.
WEBPAGE
Storage Refresh Assessment
Visibility to control rising SSD costs, delay storage purchases, reclaim primary storage, cut ransomware risk, govern sensitive data, and select the right AI-ready data.
Frequently Asked Questions
Why is unstructured data management essential for media and entertainment organizations?
Media and entertainment companies generate some of the largest and fastest-growing volumes of unstructured data of any industry. Raw footage, VFX renders, audio masters, transcoded proxies, and archived productions accumulate across petabytes of NAS and object storage. Most of this content goes cold quickly after a project wraps, yet it occupies expensive primary storage indefinitely without a systematic approach to lifecycle management. With NAND flash prices forecast to surge 234% in 2026, the cost of inaction is now a budget emergency for studios, broadcasters, and post-production organizations.
Unstructured data management gives media IT teams global visibility across all storage environments, the ability to tier cold content automatically without disrupting workflows, and the metadata intelligence needed to support content discovery, licensing, and AI initiatives across petabyte-scale libraries.
Why is media metadata so difficult to manage at scale?
Media metadata including EXIF, XMP, IPTC, codec, resolution, frame rate, and color space is often embedded inside the file itself rather than stored in the file system. Once a file is transcoded, moved, or archived, this embedded metadata can become disconnected or lost entirely, making content impossible to find without expensive manual tagging. As content libraries grow into the millions of assets, manual metadata workflows become unscalable and create gaps in content discoverability, rights management, and AI data preparation.
Automated metadata extraction at petabyte scale requires a platform specifically designed for unstructured file and object data, not a database or manual tagging system. Without it, media organizations are unable to monetize their archive, prepare content for AI workflows, or meet content delivery timelines efficiently.
How does Komprise help media and entertainment companies control storage costs?
Komprise scans across all NAS and cloud storage environments to identify cold and inactive media assets, then automatically tiers them to lower-cost cloud or object storage based on policy. Tiered assets remain accessible via Dynamic Links from their original paths with no disruption to editors, producers, or archive teams and no rehydration required. Komprise customers consistently reclaim 70% or more of primary storage capacity, with additional savings from reduced backup and DR costs on tiered content. The Komprise Flash Stretch Assessment quantifies the savings opportunity in your specific environment before any hardware commitment is made.
KAPPA data services provide customizable, automated extraction of embedded media metadata including EXIF, XMP, IPTC, codec, resolution, and media order information at petabyte scale. Extracted metadata is stored in the Global Metadatabase as searchable custom tags, enabling production teams and AI workflows to find and use media assets based on rich content-level criteria rather than file system attributes alone.
How does Komprise support AI and analytics workflows for media organizations?
AI workflows for content tagging, scene detection, subtitle generation, and multimodal search require media data to be accessible, well-classified, and delivered without manual data engineering for each project. Without a unified metadata index across distributed storage environments, AI teams cannot reliably find or curate the right assets, and models process noise alongside valuable content, inflating inferencing costs and degrading output quality.
Komprise Intelligent AI Ingest uses the Global Metadatabase to deliver precisely the right media files to AI platforms automatically rather than copying entire NAS volumes. Precise curation based on metadata and custom tags, including EXIF, codec, resolution, and media order attributes extracted by KAPPA, ensures AI pipelines receive targeted, governed datasets rather than broad directory dumps. This reduces the volume of irrelevant content models must process and boosts AI ROI by delivering only the media assets that are relevant to each specific workflow.
Why should media and entertainment organizations use Komprise over alternatives?
Storage-vendor tiering tools are limited to a single vendor’s platform, use proprietary formats that require costly rehydration when switching vendors, and have no awareness of media-specific metadata or production group policies. For organizations managing multi-petabyte content libraries across multiple NAS vendors and cloud providers, this creates both cost and flexibility constraints that compound over time.
Komprise is designed and used by the most demanding media organizations because it works across all storage and clouds, stores tiered content in native format with no rehydration penalty or vendor lock-in, supports flexible tiering policies per production group or project, and provides the metadata enrichment and AI data pipeline capabilities that media IT teams need to support both cost optimization and content monetization goals.
Ready to Bring Structured to Your Unstructured Data?
Schedule a call with our unstructured data management experts and see your file and object data in a whole new way.
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