SPLUNK .CONF, DENVER, September 15, 2026 – As AI agents take on more of the work inside the enterprise, the biggest barrier to adoption isn’t capability – 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.
“One of the biggest roadblocks to enterprise AI today is that it’s too hard to deploy,” said Jeetu Patel, President and Chief Product Officer, Cisco. “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.”
Self-managed Splunk AI, accelerated by NVIDIA
For customers who can’t move sensitive data to the cloud, Splunk AI has remained out of reach – 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.
- 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 – 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.
- 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.
- 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.