What if you could see every corner of your AI powered systems, predict issues before they arise, and deliver seamless digital experiences, all while fortifying your cybersecurity defenses? Splunk and Cisco are bringing that outcome within reach through a suite of platform, observability, and security advancements that help teams move faster with confidence in an agentic AI world. The shared objective is straightforward. Put trusted data and practical AI to work where it matters most, so organizations can elevate customer experiences, reduce risk, and operate efficiently at scale.
The collaboration centers on turning data into resilient operations. As enterprises modernize applications and adopt AI agents, complexity increases and blind spots multiply. The new capabilities from Splunk and Cisco are designed to remove those gaps. They bring together operational telemetry, security context, and user behavior insights in a way that is easier to deploy in highly regulated and distributed environments, including sovereign cloud and compliance driven settings.
Splunk Accelerates Agentic AI Innovation at Cisco Live Amsterdam
At the heart of the announcement is progress across the Splunk Platform. Splunk is introducing hosted AI models that provide out of the box analytics and reasoning, predictive alerting, and anomaly detection. By pairing curated models with an organizations data, teams can accelerate time to insight without heavy integration or model management overhead. These models are complemented by the Splunk Model Context Protocol, commonly called MCP, which is now generally available. MCP helps AI systems securely tap into Splunk capabilities with a standardized approach, so workflows can be simplified and cross domain insights can be gained with less custom work.
Another key update is a native Splunk platform integration with Cisco Nexus One, planned for availability in March. With this integration, customers can analyze telemetry within their operational boundaries rather than exporting data to external systems. For public sector, financial services, healthcare, and other regulated industries, this approach supports sovereign cloud deployments and compliance requirements while still unlocking rich analytics. It also reduces data movement and associated cost, while helping security and operations teams work from a consistent source of truth.
A unified vision for resilient AI powered digital operations
Agentic AI changes how software is built, deployed, and managed. Systems increasingly make decisions and take actions on behalf of users. The combined innovations from Splunk and Cisco reflect this shift. They prioritize visibility into agents and large language model enabled applications, clarity about costs and performance, and strong control points that keep human experts in charge. The result is a practical framework for adopting AI that is grounded in evidence and measurable outcomes rather than hype. It is about enabling teams to set policies, monitor adherence, and tune models and agents with clear feedback loops.
Advancements in the Splunk Platform
The Splunk Platform now offers hosted AI models available beginning on February 18. These models provide built in reasoning capabilities for operational analytics, speeding up root cause analysis and improving the quality of alerting without lengthy setup. The Splunk Model Context Protocol is generally available and offers a secure, standardized method for AI systems to connect to Splunk searches, knowledge objects, and data. This makes it easier to build assistants and agents that can reason over logs, metrics, traces, and security data in context. The native integration with Cisco Nexus One, available in March, lets customers process network and infrastructure telemetry in place, supporting data residency and governance policies while still accessing Splunks analytics and visualization layers.
Agentic Observability that keeps humans in control
Observability teams can extend their reach with new agentic focused capabilities. AI agent monitoring for Splunk Observability Cloud, available beginning on February 25, gives teams the ability to measure performance, quality, cost, and security of large language model and agentic applications. That means clear visibility into model behavior, latency, error rates, token consumption, and policy adherence. In parallel, Splunk digital experience analytics, available in March, unifies behavioral analytics and observability data. With a single Open Telemetry agent, teams can track feature usage, user flows, conversion, and experience metrics in context with backend traces and metrics. The combined view connects what users experience to what services and models are doing behind the scenes.
Agentic Security for faster detection and response
Security operations centers face an expanding attack surface as AI models interact with data and users. Splunk Enterprise Security Premier Edition is now generally available to help meet that challenge. It merges Splunk security capabilities, including security orchestration and response, user and entity behavior analytics, and threat intelligence, into a single analyst experience that is AI assisted. The goal is to reduce mean time to detect and respond, improve analyst throughput, and lower organizational risk. With embedded AI that is grounded in the organizations telemetry and security knowledge, teams can triage alerts more effectively, automate common tasks with confidence, and retain human oversight for critical decisions.
Built for regulated and sovereign environments
Many enterprises must balance rapid innovation with strict data controls. The native Splunk integration with Cisco Nexus One allows telemetry to be analyzed without exporting data to external systems. This approach supports sovereign cloud scenarios and compliance programs while preserving deep analytics. Combined with MCPs standardized and secure connectivity, organizations can adopt AI assistants and agents while maintaining control over where data resides and how it is accessed. This is especially important for industries that face stringent audit and reporting requirements. The aim is to enable progress without sacrificing governance.
Real world momentum including Webster Bank
Enterprises across sectors are already putting these capabilities to work. Webster Bank, for example, has shown how a data driven approach to operations and security can improve service quality while managing risk. By consolidating telemetry, enriching context, and adopting automation thoughtfully, teams can spot patterns earlier, cut manual effort, and focus on higher value investigations. That is the practical promise of agentic AI when combined with the right data foundation and controls. It is not about replacing human expertise. It is about giving teams better evidence and faster feedback so they can make sound decisions.
How to get started
Organizations exploring AI assisted operations and security can begin by identifying the questions that matter most to their customers and their risk posture. Then align data sources, define policies, and choose the capabilities that deliver fast wins. Hosted AI models in the Splunk Platform can jumpstart analytics and alerting. MCP can streamline how AI assistants access context safely. Agent monitoring and digital experience analytics can clarify where to optimize experience and cost. Enterprise Security Premier Edition can bring response automation and behavior analytics into a cohesive workflow. For a deeper look or to discuss fit for your environment, connect with Splunk or your Cisco representative to map a plan aligned to your goals and compliance needs.
The path forward is clear. As agentic AI becomes part of everyday operations, resilience depends on trustworthy data, observable systems, and strong security. Splunk and Cisco are working together to make that foundation easier to achieve so that teams can deliver reliable experiences, predict and prevent issues, and keep defenses strong. The focus is practical, measurable outcomes that help organizations move with speed and control.
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