Cisco leverages Splunk for new scalable AI solutions

This week, Cisco announced some new security-focused capabilities via Splunk, with an emphasis on the AI-powered agents that many organisations are looking to integrate into their environments.

With trust of said agents being a key concern, Cisco is making new solutions available aimed at giving customers the ability to safely and cost-efficiently scale AI wherever their data already lives.

Added to this, Cisco is also expanding its partnership with NVIDIA in order to bring Splunk AI to on-premises customers.

“One of the biggest roadblocks to enterprise AI today is that it’s too hard to deploy. Customers 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,” noted Jeetu Patel, president and chief product officer at Cisco, in a release shared with Hypertext.

There are three new developments in particular that Cisco has highlighted regarding Splunk AI, which is now being made more readily available to enterprise customers.

Here, Cisco Secure AI Factory with NVIDIA is framed as the reference architecture that brings the full AI stack together, with it being built from Cisco AI PODs. These are the newest configurations from the company, with Cisco AI POD for Splunk, bringing Splunk AI to on-premises customers.

This specific solution includes, “new AI runtime software, Cisco infrastructure, NVIDIA accelerated computing, and Kubernetes-based architecture – pre-validated and optimized for Splunk AI Cisco Confidential workloads.”

The company confirmed that Cisco AI POD for Splunk are available right now. Furthermore, Cisco noted that for customers who have their own infrastructure, partners like bitsIO, Wipro, and World Wide Technology are ready on day one to help customers deploy it.

One of the other key announcements involved Splunk AI Assistant, which too is available now, and Agent Launchpad, which is expected later this year. These two solutions are designed to work in tandem, and together, they bring ad-hoc agentic investigations and custom agent building for a broad variety of use cases, according to Cisco, including the agentic SOC to teams that run Splunk in their own data centres.

The third notable announcement comes in the form of customers being able to self-host a selection of open and proprietary generative AI models for their Splunk Enterprise workloads. These include the Cisco Deep Time Series Model, Google Gemma 4, and OpenAI GPT-OSS 20B, with NVIDIA Nemotron open models planned for the coming months. “Teams can use the model best suited for the job without sending data outside their environment,” shared Cisco.

“Enterprises need to bring AI where their data lives, especially when security and sovereignty requirements require critical workloads to stay on-premises. By 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,” enthused Justin Boitano, VP of Enterprise AI at NVIDIA.

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