Cisco Secure AI Factory with NVIDIA unlocks enterprise data for agentic AI
Cisco Secure AI Factory with NVIDIA unlocks enterprise data for agentic AI
Cisco unveiled a solution to help enterprises turn their data into secure, AI-ready fuel for agentic workflows at scale. The Cisco Secure AI Factory with NVIDIA now supports workload data fabrics that speed retrieval-augmented generation (RAG) pipelines, giving AI agents instant, governed access to business information while keeping every token protected with Cisco AI Defense. The announcement highlights a fully integrated offering with VAST Data, built on the NVIDIA AI Data Platform reference design, to accelerate data extraction and retrieval for near-real-time AI responses.
News summary: Cisco will offer a validated solution with VAST Data to enable faster data extraction and retrieval for agentic AI. Cisco AI PODs leverage VAST InsightEngine to provide an NVIDIA AI Data Platform solution that delivers real-time data pipelines for the Secure AI Factory. The architecture extends Secure AI Factory capabilities across more use cases, helping speed enterprise AI adoption while maintaining security and governance.
What’s new: Cisco AI PODs—the AI infrastructure building blocks of the Secure AI Factory—are now available with VAST InsightEngine, a core capability of VAST Data AI OS. Using the NVIDIA AI Data Platform reference design, the PODs transform raw data into AI-ready datasets. Within the PODs, the Cisco UCS server portfolio paired with NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs delivers high performance for next-generation AI applications. RTX PRO Servers from Cisco are among the first systems to deliver the NVIDIA AI Data Platform reference design.
Performance and connectivity: NVIDIA accelerated computing and AI software enable low-latency model interaction, and Cisco high-performance ethernet networking moves data and compute seamlessly. Together, this unified stack supports agents operating on near-real-time insights with the security, governance, and flexibility of the Cisco Secure AI Factory with NVIDIA architecture. Customers can also gain unique visibility with Splunk and apply safety and security guardrails to every token using Cisco AI Defense.
Executive perspective:
“Agentic AI has the potential to unlock the value of AI for enterprises around the world. Moving beyond chatbots to agents that can help solve true business challenges is revolutionary, but only if enterprises can effectively leverage the right data at the right times. Cisco, NVIDIA and VAST are working together to give customers a simple path to unlocking the value of their data,” said Jeremy Foster, senior vice president and general manager, Cisco Compute. “We are designing the architecture for how the enterprise will build the next generation of AI factories.”
“The next wave of agentic AI will be fueled by enterprise data, enabling agents to tap into business knowledge during inference for precise, up-to-date insights,” said Justin Boitano, vice president, Enterprise AI at NVIDIA. “Bringing together Cisco Secure AI Factory with NVIDIA and VASTInsightEngine creates an integrated platform for running powerful AI agents at scale.”
“By integrating the VAST Data InsightEngine into the Cisco Secure AI Factory with NVIDIA, we’re giving enterprises the first integrated design for RAG acceleration at scale,” said John Mao, vice president of strategic alliances at VAST Data. “This collaboration with Cisco and NVIDIA represents a major milestone in the evolution of enterprise AI. The integration of the VAST InsightEngine into the Secure AI Factory architecture sets the stage for a new era where intelligent agents can operate securely, collaboratively, and at unprecedented scale.”
An architecture for enterprise agentic AI:
Agentic AI workloads demand infrastructure that removes data bottlenecks, lowers latency, and enforces strong security and governance. Enterprises want agents that can collaborate with knowledge workers and other agents to tackle complex tasks; doing so requires workload data fabrics that supply the right data at the right moment—securely.
What customers can expect now:
- Faster time to insights: Reduce RAG pipeline latency from minutes to seconds to support near-real-time AI responses.
- Agentic AI at enterprise scale: High-throughput data unlocks multi-step reasoning while supporting multiple agents and workloads simultaneously.
- Security and governance by design: Role-based access control plus compliance and audit readiness help protect sensitive information while accelerating AI innovation.
Availability: Cisco AI PODs with VAST InsightEngine, offering an NVIDIA AI Data Platform solution, are orderable from Cisco now. The AI POD designed for RAG acceleration with NVIDIA and VAST is the first in a series of AI services PODs built to support a growing range of enterprise use cases.
Source here – Have a Story? Address it to the Editor and submit it here
About Cisco’s Compute business unit
Cisco’s Compute business unit plays a central role in the company’s strategy to build secure, scalable digital infrastructure for enterprises. Led by Jeremy Foster, Senior Vice President and General Manager, the division oversees Cisco’s Unified Computing System (UCS) portfolio, AI infrastructure products, and server innovations that power next-generation workloads. Its mandate is to integrate high-performance computing with networking, storage, and security into validated architectures that enterprises can deploy with confidence.
The team is responsible for delivering Cisco AI PODs, the modular building blocks of the Secure AI Factory, and ensuring interoperability with NVIDIA GPUs, advanced ethernet networking, and partner technologies such as VAST Data InsightEngine. Beyond raw performance, Cisco Compute emphasizes governance, compliance, and role-based access to data, aligning AI adoption with enterprise risk management. By designing architectures for agentic AI and secure workload data fabrics, Cisco Compute defines how organizations can run AI factories at enterprise scale.
Featured Image: Cisco
Disclaimer
The information provided in this article is for general informational purposes only and from publicly available sources. While we strive for accuracy, we do not make any representations or warranties, express or implied, regarding the completeness, reliability, or validity of the content. This article does not make any direct claims about specific companies, individuals, or organizations. Any references to reports or external sources are for context and do not imply endorsement or verification of any specific allegations. Readers are encouraged to conduct their own research and seek professional advice before making business decisions. We disclaim any liability for any losses or damages incurred as a result of reliance on the information provided.