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NetApp's strategy focuses on enabling AI workloads directly within existing legacy storage environments rather than requiring costly infrastructure migrations or data re-architecting. By unifying file, block, and object storage with built-in governance and protection layers, the platform aims to reduce data silos while maintaining accessibility for production AI models. This approach addresses a critical bottleneck in enterprise AI adoption: leveraging vast historical datasets without disrupting current operational workflows.
NetApp aims to make legacy data AI-ready without a rebuild
Enterprises sitting on decades of legacy information face a pressing question as artificial intelligence moves from pilots to production: Can that archive become AI-ready data without a costly rebuild of the infrastructure underneath it? NetApp Inc. is betting it can answer that question with a platform that reaches well beyond its storage roots. The company […] The post NetApp aims to make legacy data AI-ready without a rebuild appeared first on SiliconANGLE.
Enterprises sitting on decades of legacy information face a pressing question as artificial intelligence moves from pilots to production: Can that archive become AI-ready data without a costly rebuild of the infrastructure underneath it? NetApp Inc. is betting it can answer that question with a platform that reaches well beyond its storage roots. The company is framing its intelligent data infrastructure strategy around…
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