Introduction

On June 22, 2025, NVIDIA introduced CogStack. This new distributed memory graph system enables multiple AI models and processes to share, search, and reason over structured and unstructured data in real-time. The company refers to it as the “neural fabric” for enterprise intelligence.

CogStack is designed to run across DGX systems and Grace Hopper superchips, linking vector databases, LLM embeddings, time-series streams, and structured enterprise knowledge graphs into a single, coherent, and queryable stack. It supports real-time joins across modalities and temporal indexing.

“With CogStack, we’re collapsing the gap between data lakes and AI reasoning,” said Manuvir Das, Head of Enterprise Computing at NVIDIA.¹ “It’s not just retrieval—it’s orchestration of memory across the AI stack.”

Unlike typical retrieval-augmented generation (RAG) setups, CogStack provides persistent shared memory and supports federated graph queries across organizations within secure enclaves.

Why it matters now

• AI agents require long-term memory and cross-context reasoning to evolve beyond single-session chat.
• Enterprises are struggling to unify siloed data across clouds and formats.
• CogStack creates a shared memory substrate where agents can “think together” and learn iteratively.

Call-out: Memory is the new compute

In NVIDIA’s internal benchmarks, CogStack improved multi-agent task accuracy by 63% in complex enterprise workflows involving live data fusion.

Business implications

• Financial firms gain event-aware agents that recall regulatory context across trades and transactions.
• Manufacturers can enable AI copilots that learn from live machine telemetry and past maintenance records.
• Developers get GraphQL-style query interfaces to embed CogStack intelligence into custom apps.

Early adopters include SAP, Bloomberg, and Lockheed Martin, all of which are piloting CogStack integrations for AI-assisted decision support and multi-agent task flow orchestration.

Looking ahead

NVIDIA plans to open parts of the CogStack SDK to the PyData ecosystem later this year and is working with Hugging Face to provide adapters for open-weight models. Cloud-hosted CogStack services will debut on NVIDIA NIM in Q1 2026.

Gartner projects that by 2027, 30% of enterprise AI deployments will depend on shared memory graphs—up from less than 4% today.

The upshot: With CogStack, NVIDIA bets that in the age of agentic AI, memory—not just models—will define enterprise intelligence. A neural fabric woven from data and context may prove to be the next trillion-dollar disruptor.

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¹ M. Das, NVIDIA Enterprise Briefing, June 22, 2025.