Hammerspace has officially announced the general availability of its new AI Data Platform (AIDP), a turnkey solution designed to remove one of the most persistent barriers in enterprise AI adoption seamless access to distributed data. As organizations continue to invest heavily in AI initiatives, many still struggle to move projects from pilot to production due to fragmented data environments and complex data preparation processes. Therefore, Hammerspace aims to simplify this transition by enabling organizations to make their existing data AI-ready without the need for costly migrations or duplication.

Unlike traditional approaches that rely on copying and moving large volumes of data into centralized systems, Hammerspace takes a fundamentally different route. Instead, it allows enterprises to leverage data in place across edge devices, data centers, and cloud environments. As a result, organizations can avoid building entirely new AI storage infrastructures while significantly reducing operational complexity and costs.

“Hammerspace is the only AI Data Platform that can access data anywhere across edge devices, data centers and clouds, across high-performance file and object storage, without forcing enterprises into a copy-first AI silo,” said David Flynn, Hammerspace Founder and CEO. “We overcome data gravity by continuously identifying the data that matters, orchestrating it efficiently to GPUs, and enabling processing where it’s most optimal, whether that’s local GPU resources near the data or centralized GPUs at scale.”

One of the biggest challenges enterprises face today is data fragmentation. Typically, teams spend significant time identifying, organizing, and preparing unstructured data for AI models. Moreover, this effort is often duplicated across departments due to siloed systems. However, Hammerspace addresses this issue by offering a unified data layer that spans heterogeneous environments. Consequently, it automates the entire pipeline required to transform raw data into AI-ready assets, improving efficiency and reducing redundancy.

In addition, the platform eliminates the need for large-scale data migrations, which are often time-consuming and resource-intensive. By enabling direct access to distributed datasets, organizations can accelerate both time-to-value and time-to-insight. Furthermore, Hammerspace minimizes unnecessary data duplication by continuously cataloging data and intelligently moving only what is required, when it is required. This approach ensures better governance, improved compliance, and optimized performance across AI workflows.

To strengthen its enterprise readiness, Hammerspace collaborated closely with SHI during the development and validation phases. SHI leveraged its AI and Cyber Lab to test integrations and demonstrate real-world value for enterprise-scale AI deployments.

“AI data preparation shouldn’t require a costly rebuild of the data estate,” said Jack Hogan, VP of Advanced Solutions at SHI. “As a key development and testing partner, we used SHI’s labs to validate that the Hammerspace AI Data Platform on Cisco UCS, with its logical visibility to distributed data, can drastically reduce data complexity. SHI is excited to offer this solution to customers because we can design it into their current architecture, integrate with their preferred infrastructure and security controls and deliver a faster path to production AI.”

Furthermore, Hammerspace has built a robust ecosystem of technology integrations to deliver a complete end-to-end AI solution. Its partnership with NVIDIA ensures compatibility with advanced GPU infrastructure and AI software frameworks, enabling high-performance computing for AI workloads. The platform supports NVIDIA AI Enterprise tools, including NIM microservices and NeMo Retriever, to streamline data orchestration and accelerate AI model deployment.

“Enterprises require a unified data foundation capable of overcoming the friction of data gravity to power today’s complex, distributed AI pipelines,” said Jason Hardy, Vice President of Storage Technologies at NVIDIA. “Built on the NVIDIA AI Data Platform, Hammerspace enables organizations to seamlessly scale from early experimentation to high-performance, production-grade AI — accelerating time to insight and unlocking the full value of their data.”

Additionally, the integration with Secuvy’s Data Security Posture Management (DSPM) technology ensures that security, compliance, and governance are embedded throughout the data lifecycle. This is particularly critical for organizations operating in regulated industries where maintaining data integrity and compliance is essential.

“For a true end-to-end AI solution, security and governance must be native to the data platform,” said Mike Seashols, CEO of Secuvy. “Integrating Secuvy’s DSPM capabilities directly with Hammerspace ensures that as AI-ready data is prepared and moved across the enterprise, security posture and compliance are automatically maintained. This approach is a game-changer for enterprises deploying AI in regulated industries.”

Overall, Hammerspace’s AIDP represents a significant step forward in simplifying enterprise AI adoption. By eliminating data silos, reducing complexity, and enabling real-time data orchestration, the platform allows organizations to scale AI initiatives more efficiently and securely. As AI continues to evolve, solutions like AIDP will play a crucial role in bridging the gap between experimentation and full-scale production deployment.

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