\n
Customers can now run, defend, and observe AI where their machine data already lives
\nCisco and NVIDIA extend partnership to bring agentic AI to Splunk on-premises customers<\/p>\n
\nAs AI agents take on more of the work inside the enterprise, the biggest barrier to adoption isn\u2019t capability \u2013 it’s confidence. Customers need to trust that AI is secure, governed, and worth the cost before they let it run at scale. Today, Cisco closes that gap through new Splunk innovations, giving customers the ability to safely and cost-efficiently scale AI wherever their data already lives. This includes an expanded partnership with NVIDIA to bring Splunk AI to on-premises customers.<\/p>\n
\u201cOne of the biggest roadblocks to enterprise AI today is that it\u2019s too hard to deploy,\u201d said Jeetu Patel, President and Chief Product Officer, Cisco. \u201cCustomers want to know: Can I trust it to do the job? Can I afford it? And, most importantly, can I secure it? By running Splunk AI on the infrastructure customers already trust, they can move faster to put AI to work in their business with confidence and control.\u201d<\/p>\n
Self-managed Splunk AI, accelerated by NVIDIA
\nFor customers who can\u2019t move sensitive data to the cloud, Splunk AI has remained out of reach \u2013 until now. Cisco and NVIDIA are expanding their partnership to bring self-managed AI directly to Splunk Enterprise customers, across their own on-premises, private cloud, and air-gapped environments.<\/p>\n
\u2022 Cisco Secure AI Factory with NVIDIA is the reference architecture that brings the full AI stack together, built from Cisco AI PODs. The newest of these configurations, Cisco AI POD for Splunk, brings Splunk AI to on-premises customers with new AI runtime software, Cisco infrastructure, NVIDIA accelerated computing, and Kubernetes-based architecture \u2013 pre-validated and optimized for Splunk AI workloads. Cisco AI POD for Splunk is available today. For customers who have their own infrastructure, partners like Accenture, bitsIO, Wipro and World Wide Technology are ready on day one to help customers stand it up.
\n\u2022 Splunk AI Assistant (available now) and Agent Launchpad (coming later this year) run on this layer. Together, they bring ad-hoc agentic investigations and custom agent building for a broad variety of use cases including the agentic SOC to teams that run Splunk in their own data centers.
\n\u2022 Customers can also self-host a selection of open and proprietary generative AI models for their Splunk Enterprise workloads, including the Cisco Deep Time Series Model, Google Gemma 4, and OpenAI GPT-OSS 20B, with the NVIDIA Nemotron open models in the coming months. Teams can use the model best suited for the job without sending data outside their environment.<\/p>\n
\u201cEnterprises need to bring AI where their data lives, especially when security and sovereignty requirements require critical workloads to stay on-premises,\u201d said Justin Boitano, Vice President of Enterprise AI at NVIDIA. \u201cBy enabling Splunk AI workloads to run with NVIDIA Nemotron open models on NVIDIA accelerated computing, Cisco and NVIDIA are working together to bring AI agents directly to Splunk and giving organizations a high-performance, full-stack foundation for agentic security operations wherever they run their infrastructure.\u201d<\/p>\n
Observe agent performance and track token spend in one view
\nNew observability innovations give Cisco customers one full-stack view into how their AI agents are actually performing.<\/p>\n
AI agents behave in ways that the people running them can\u2019t always predict, running up costs that stay invisible until the invoice lands. Splunk Agent Observability, with its new Tokenomics capabilities, is closing that visibility gap and giving organizations a real-time view into agent performance and AI token spend. This enables teams to see exactly where and why AI costs accumulate before they become a budget problem.<\/p>\n
Splunk Agent Observability, announced initially as an on-premises offering, is now available in Splunk Observability Cloud and in Cisco Cloud Control, extending visibility to customers working across the Cisco portfolio. It evaluates agent and model behavior, observes performance across the AI stack, and applies runtime guardrails that block inaccurate or unsafe actions, like hallucinations or leaking sensitive data.<\/p>\n
As part of Splunk Agent Observability, the new Tokenomics solution extends that visibility to spend \u2013 tracking and attributing token expenditure across AI agents and employees\u2019 use of coding agents like Claude Code, Codex, and Cursor. It will also forecast consumption patterns to project where spend is headed before a billing period ends, using the Cisco Deep Time Series Model. These insights help organizations to operationalize a tokenomics framework and tie AI spend to business outcomes.<\/p>\n
Cisco is also helping organizations strengthen their infrastructure resilience by minimizing visibility gaps and cost barriers that hinder autonomous troubleshooting. The Observability Studio enables teams to ensure new applications are \u201cborn observable,\u201d measurable and production-ready from the start. The new Network Intelligence App brings Cisco network topology, device health, and events into Splunk, so network teams can trace an alert straight to the device behind it and the network around it. Also, the new editions for Observability Cloud \u2013 Essentials and Premier \u2013 simplify how customers buy and expand observability across their business, with cost-effective log analytics to debug application and infrastructure problems.<\/p>\n
Trusted autonomy for the Agentic SOC
\nAI-driven attacks are moving faster than traditional, human-led security operations can respond. Stopping them requires an agentic SOC capable of reasoning and defending at machine speed, without compromising the data sovereignty and human governance enterprise leaders demand.<\/p>\n
Splunk is advancing the agentic SOC by combining enterprise-wide telemetry with specialized AI agents powered by leading frontier and domain-specific models. New purpose-built agent capabilities expand the Splunk Agentic SOC Workforce and mirror how elite security operations teams work across detection engineering, proactive threat hunting, autonomous investigation, coordinated response, and policy governance. By correlating rich, full-stack machine data across network, cloud, application, and identity environments, these agents deliver deep reasoning and transparent, explainable verdicts that cut alert noise and accelerate mean time to remediate.<\/p>\n
Attackers are now using AI to hunt for vulnerabilities at scale, probing infrastructure, applications, and identity systems continuously and indiscriminately. Recent exploitation campaigns have made complete exposure visibility a board-level requirement. New Exposure Analytics enhancements deliver it with broader asset coverage, historical change tracking, and business-specific risk insights. Connecting exposure context to live security activity across Splunk, Cisco, and an extensive third-party ecosystem, so teams see their entire estate rather than one vendor\u2019s slice of it. Agents use that context to pinpoint what matters most and where risk is active.<\/p>\n
New capabilities in Splunk Enterprise Security Essentials bring agentic security operations and greater autonomy to far more security teams. Splunk Enterprise Security Premier adds deeper agentic autonomy and the full power of Splunk Enterprise Security.<\/p>\n
Building the Agentic Enterprise together: Cisco\u2019s Splunk and AWS
\nThe same urgency is driving Splunk\u2019s next chapter with AWS. Splunk and AWS are expanding their long-standing relationship into joint product development through a multi-year agreement. The work advances the agentic SOC to match the speed of AI-driven attacks.<\/p>\n
Those attacks now move faster than human-led response processes can answer. Matching that speed takes deep security intelligence and the scale to act on it instantly. Splunk brings the data platform and detection depth security teams already run on. AWS brings global cloud scale. Together they will put agentic support in the hands of analysts across detection, investigation, and response.<\/p>\n
Security teams won\u2019t give up oversight to move faster. What\u2019s ahead is agentic action at scale, with the governance and analyst control enterprises require.<\/p>\n","protected":false},"excerpt":{"rendered":"
Customers can now run, defend, and observe AI where their machine data already lives Cisco and NVIDIA extend partnership to bring agentic AI to Splunk on-premises customers As AI agents take on more of the work inside the enterprise, the biggest barrier to adoption isn\u2019t capability \u2013 it’s confidence. Customers need to trust that AI …<\/p>\n","protected":false},"author":2,"featured_media":135602,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[439],"tags":[],"class_list":["post-135601","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-english-news"],"yoast_head":"\n