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Beyond storage: Everpure’s bet on data primacy

Coen or Sander Season 3 Episode 16

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0:00 | 24:53

At its own Accelerate event, Everpure did several important strategic announcements. The company is expanding its platform on top of what it already has and is going to compete with quite a number of companies outside the storage space. To talk more about this, we talked to Prakash Darji, General Manager, Digital Experience at Everpure and hear more about why the company is expanding well beyond its storage roots.

The introduction of Universal Data Intelligence marks a strategic shift toward helping enterprises manage data independently of applications. Everpure makes this move driven by the architectural demands of AI agents, large language models, and the need for data primacy across the entire enterprise.

Darji walks through the two core components of Universal Data Intelligence. First there's Data Intelligence (formerly 1touch, acquired earlier this year), which catalogs, classifies, and contextualizes data across every source, from block/file/object storage to SaaS platforms like Salesforce, ServiceNow, and Workday. The second component is Data Stream. This vectorizes relevant data and prepares it for AI consumption.

Together, Data Intelligence and Data Stream should form an end-to-end portfolio that also spans FlashBlade S and FlashBlade X for deployment at any scale. A key differentiator is Everpure's middleware approach. Rather than asking customers to move all their data into one ecosystem, the platform builds a knowledge graph of relationships and metadata, pointing back to original sources.

The conversation we have with Darji also gets into the competitive landscape. Because Everpure is going up against some formidable opponents. However, Darji argues that vendors like SAP, Salesforce, Databricks, and Snowflake are all pushing self-serving "give us your data" strategies that don't hold up in real-world multi-system environments. Everpure's answer is data primacy. This means treating data as the primary layer on which applications and AI agents operate, rather than the other way around. The interview closes with a forward-looking discussion on how new applications will be built on shared data schemas, with workflows replacing traditional application integrations.

• Universal Data Intelligence combines Data Intelligence and Data Stream for end-to-end AI readiness
• Data Intelligence catalogs and contextualizes data across all sources without replicating it
• Only ~15% of enterprise data is truly useful. Finding the relevant subset improves AI accuracy and reduces token costs
• Data Stream vectorizes data for AI consumption; integration with Data Intelligence ensures only relevant data is prepared
• A knowledge graph tracks relationships and lineage across systems without storing the underlying data
• Everpure's middleware approach contrasts with ecosystem-lock-in strategies from SAP, Salesforce, Databricks, and Snowflake
• Portworx remains app-centric and will need to evolve toward data primacy to fit the new strategy
• Future applications will be built as workflows on top of shared data schemas, not as isolated systems

0:35 Pure Storage's new direction beyond storage
1:15 Introducing Universal Data Intelligence
2:31 Finding the right data: relevance and primary sources
6:46 Context, ontologies and knowledge graphs
15:00 Data Stream: vectorization and data prep explained
16:30 Navigating a crowded competitive landscape
20:57 Data primacy: moving beyond data-centricity
22:51 The future: data schemas, workflows, and AI agents