Cisco Expands Splunk AI Across Enterprise Infrastructure
Cisco Expands Splunk AI Across Enterprise Infrastructure
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Key Points
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Splunk’s tokenomics capabilities build on Cisco’s acquisition of Galileo, which helps analyze AI agents at the behavioral level; Splunk combines model and GPU data to assess performance and calculate the tokens used for individual AI actions.
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Splunk executive Kamal Hathi said the company aims not only to measure token use but also to actively control costs, align consumption with business priorities and provide prescriptive recommendations without sacrificing quality.
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Cisco says Native Splunk in Nexus One is designed to reduce the need to move all operational data into a centralized platform, helping limit data gravity, latency, costs and the number of copies of sensitive information that must be governed.
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Cisco AI POD for Splunk is based on Red Hat OpenShift and combines Cisco compute infrastructure, Nvidia GPU acceleration and Splunk software, allowing customers to run tools such as AI Assistant and AI Toolkit inside an environment they control.
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The partnership announcement comes as Cisco’s market valuation raises the execution stakes: one cited comparison put the company’s share price at $110.395, or 48.38% above a $74.40 GF Value estimate, increasing pressure for AI POD and related offerings to achieve meaningful customer scale and recurring economics.
Cisco is expanding Splunk's artificial intelligence tools to help enterprises manage AI workloads more effectively. The company launched Splunk Agent Observability to track AI token use and costs, plus Cisco AI POD for Splunk to let customers run AI tools on their own infrastructure. Verdict reported that these moves combine Cisco's compute power, Nvidia's graphics processors, and Splunk's analytics to give enterprises better control over where and how they deploy AI.
The initiatives address a key challenge facing large companies: understanding what AI costs and where it runs. According to CXO Today, Splunk executive Kamal Hathi said the goal is not just to measure token consumption but to actively control costs and align AI usage with business priorities. ITWire noted that the new systems reduce unexpected expenses and operational risks as enterprises scale artificial intelligence across their operations.
Splunk Agent Observability Tracks AI Spending and Performance
Splunk Agent Observability monitors how much AI costs in real time. The tool tracks tokens used by AI models such as Claude and Codex, measuring both spending and productivity ITWire reported. Cisco's forecasting feature estimates bills before each billing cycle ends, helping teams spot overages early.
This builds on Cisco's 2024 acquisition of Galileo, which analyzes how AI agents behave. CXO Today explained that Splunk combines model data and GPU performance metrics to show exactly which AI actions consumed which tokens. Hathi stated the company aims to provide prescriptive recommendations that control costs without sacrificing AI quality.
Cisco Extends Splunk Across Multi-Node Enterprise Networks
Cisco expanded Native Splunk in Nexus One from single-node to multi-node deployments. CXO Today noted this lets enterprises combine network telemetry with application, infrastructure, and security data all at once. The upgrade speeds investigations and root-cause analysis by unifying multiple data types.
The multi-node capability reduces data gravity—the problem of moving vast amounts of data to one central location. Technology Decisions reported that keeping data closer to where it lives cuts latency, lowers costs, and limits how many copies of sensitive information need protection and governance.
On-Premises AI POD Puts Control in Customer Hands
Cisco AI POD for Splunk lets enterprises run Splunk's AI Assistant and AI Toolkit inside their own computing environment using Red Hat OpenShift. Verdict explained the system combines Cisco compute infrastructure with Nvidia GPU acceleration. Customers retain full control over their AI infrastructure and data.
Technology Decisions highlighted that confidence is the biggest barrier to AI adoption. Many enterprises hesitate to move AI into production without knowing their data stays protected. The on-premises POD addresses this by letting teams deploy and monitor AI on hardware they own and manage directly.
Cisco and Nvidia Deepen AI Infrastructure Partnership
Cisco and Nvidia renewed their collaboration to combine Nvidia's AI infrastructure with Cisco's networking technology for Splunk analytics. Verdict reported the partnership adds Nvidia GPU acceleration to Cisco's broader push to sell integrated networking, infrastructure, and Splunk software as one package. The companies disclosed no financial terms.
These initiatives strengthen Cisco's strategy to help enterprises move AI workloads into production across their entire infrastructure. Success depends on whether customers actually adopt these tools and whether the deployment costs justify the benefits. CXO Today noted that Cisco's high valuation increases pressure on the AI POD and related offerings to achieve meaningful customer adoption and predictable revenue.
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