This demo shows how customers can cut costs, modernize their storage, and better manage their multicloud strategy with Komprise Intelligent Data Management.
This demo shows how customers can cut costs, modernize their storage, and better manage their hybrid, multi-cloud strategy with Komprise Intelligent Data Management. See how you can know and understand your data, better plan your hybrid, multi-cloud unstructured data management strategy, transparently move and manage your data across all silos without any disruption to users, and deliver the right data to AI and analytics services with Smart Data Workflows.
Komprise Intelligent Data Mangement FAQs
Why do enterprises need a dedicated unstructured data management solution for hybrid, multicloud storage?
Most hybrid, multicloud storage strategies are built around compute and structured data. Unstructured data, which makes up 80-90% of enterprise data according to Gartner and is growing 55-65% annually, is typically managed as an afterthought using native tools from individual storage vendors. The problem is that vendor-native tools only see their own platform. They cannot provide unified visibility across a NetApp NAS environment, a Dell NAS environment, and AWS S3 simultaneously. They cannot apply consistent tiering, classification, or governance policies across all environments. And they create vendor lock-in by storing tiered data in proprietary formats that cannot be read without the originating vendor’s software.
Komprise Intelligent Data Management operates independently of any storage vendor, providing a single platform for analyzing, governing, tiering, migrating, and curating unstructured data across NAS and cloud environments. This means one policy engine, one metadata index, one governance framework, and one cost optimization strategy regardless of which storage vendors are in the environment, or which ones change in the future.
Why is right now a particularly important time to address multicloud unstructured data costs?
Three converging pressures are making the cost of unmanaged multicloud unstructured data more acute in 2025 and 2026 than at any previous point.
- First, enterprise SSD and NAND flash prices rose 53-58% quarter-over-quarter in Q1 2026 according to TrendForce, driven by AI data center demand consuming available supply. Organizations with large volumes of cold unstructured data on flash-based primary storage are now paying significantly more per gigabyte than they were 12 months ago for data that has not been accessed in years.
- Second, AI initiatives are competing for the same high-performance storage capacity that cold data is occupying. Enterprises that have not addressed their unstructured data sprawl are now discovering that their AI programs are constrained by the same storage capacity problems that their standard workloads have always faced, just at higher cost and with greater urgency.
- Third, the cost of inaction compounds. Unstructured data grows 55-65% annually. Every month without a tiering and governance strategy means more cold data accumulating on expensive primary storage, more backup and replication costs for data that provides no business value, and a larger eventual cleanup project. Komprise customers who act now typically reclaim 70% or more of primary storage capacity within the first 90 days of deployment.
What makes Komprise different from storage vendor tiering tools and cloud-native lifecycle policies?
The fundamental difference is that Komprise operates at the file level with full business context, while vendor tiering tools operate at the block level with no awareness of what data actually is or who owns it. Read the paper.
A storage vendor’s native tiering tool moves data based on I/O frequency. It has no way to distinguish between a cold archive that no one will ever access again and a compliance-critical document that must remain accessible. It cannot apply policies based on file owner, project tag, department, file type, or any other business criterion. And it only works within that vendor’s own storage ecosystem.
Komprise Intelligent Tiering uses Komprise Analysis to scan the entire storage estate, build a precise picture of what data exists and how it is being used, and then apply tiering policies based on any combination of file age, owner, type, size, access history, and custom tags. Cold data is moved using Transparent Move Technology, which stores it in its native format on any cloud or object destination with no proprietary wrapping and no rehydration required. Users access tiered data transparently via Dynamic Links. Any AI pipeline or analytics tool can read tiered data directly without any recall step.
Unlike cloud-native lifecycle policies that manage data within a single cloud provider’s environment, Komprise manages data across all cloud providers and on-premises NAS simultaneously, with a unified policy engine and a single Global Metadatabase that tracks every file across every environment.
How does Komprise help enterprises prepare unstructured data for AI while also reducing storage costs?
Storage cost optimization and AI data preparation are not separate problems in most enterprise environments. They share the same root cause: too much unstructured data in the wrong place, with insufficient metadata to distinguish what is valuable from what is not.
Komprise addresses both simultaneously. Komprise Analysis identifies cold data that should be tiered off primary storage, reducing costs. Komprise Deep Analytics queries the Global Metadatabase using metadata and custom tags to identify precisely which data is relevant for a specific AI use case. Komprise Smart Data Workflows automate the curation and delivery of governed, right-placed unstructured datasets to AI platforms, with sensitive data detected and excluded before ingestion.
The result is that organizations using Komprise do not have to choose between cutting storage costs and accelerating AI readiness. Tiering cold data off primary storage frees capacity and budget for AI infrastructure. Metadata enrichment via KAPPA data services makes the remaining data more discoverable and AI-ready. Smart Data Workflows connect the two by ensuring that the right data reaches AI pipelines without manual effort or custom ETL pipelines.
Customers like NewYork-Presbyterian achieved 96% cloud cost savings and 10x faster AI data ingestion for digital pathology using Komprise, demonstrating that storage cost optimization and AI acceleration are two outcomes of the same underlying data management investment.
What should I expect from a Komprise demo and how do I get started?
A Komprise demo typically covers five areas.
- First, unified visibility: see how Komprise scans and indexes your entire unstructured data estate across all NAS and cloud environments, presenting a complete picture of data growth, cold data volumes, ownership, and storage costs in a single view without agents or changes to your infrastructure. This continuous, always-on visibility is the foundation for every other capability, and it updates automatically as your data estate changes.
- Second, transparent tiering and ongoing lifecycle management: see how tiering policies automatically move cold data to lower-cost storage on a continuous basis, not as a one-time cleanup but as an ongoing operational practice that keeps primary storage optimized as new cold data accumulates. Data remains accessible to users from its original path with no disruption, and any application or AI pipeline can read tiered data directly without any recall step.
- Third, data migration: see how Komprise takes an analytics-first approach to moving data between storage environments, identifying what should migrate to primary storage at the destination, what should be tiered to lower-cost storage during the migration, and what qualifies as ROT data that should be deleted rather than moved. This right-placement approach typically reduces destination storage costs by 70% or more compared to a traditional lift-and-shift.
- Fourth, AI data preparation: see how curated, governed datasets are built and delivered to AI platforms automatically on a defined schedule, with sensitive data detected and excluded before ingestion and a full audit trail maintained throughout. Policy-based AI data workflows run continuously, so AI pipelines always receive current, governed data rather than a one-time snapshot.
- Fifth, what-if savings modeling: see how you can quantify the storage cost savings opportunity in your specific environment before committing to any action, so you arrive at any investment conversation with data rather than estimates.
Most Komprise customers see immediate value within the first few weeks of deployment. Getting started is non-disruptive and requires no changes to existing applications, user workflows, or storage infrastructure.
To see Komprise in action with your own data profile and use cases, request a demo at komprise.com/schedule-a-demo.
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