Splunk recently announced the Splunk AI, a collection of new AI-powered offerings to enhance its unified security and observability platform. Launched at .conf23, Splunk AI combines automation with human-in-the-loop experiences, so organizations can drive faster detection, investigation and response while controlling how AI is applied to their data. Leaning into its lineage of data visibility and years of innovation in AI and machine learning (ML), Splunk continues to enrich the customer experience by delivering domain-specific insights through its AI capabilities for security and observability.
Splunk AI strengthens human decision-making and threat response through assistive experiences. The offerings empower SecOps, ITOps and engineering teams to automatically mine data, detect anomalies and prioritize critical decisions through intelligent assessment of risk, helping to minimize repetitive processes and human error.
Splunk AI optimizes domain-specific large language models (LLMs) and ML algorithms built on security and observability data, so SecOps, ITOps and engineering teams are freed up for more strategic work – helping to accelerate productivity and lower costs. Looking forward, Splunk is committed to remaining open and extensible as it integrates AI into its platform, so organizations can extend Splunk AI models or use home-grown and third party tools.
“Splunk’s purpose is to build a safer, more resilient digital world, and this includes the transparent usage of AI,” said Min Wang, CTO at Splunk. “Looking forward, we believe AI and ML will bring enormous value to security and observability by empowering organizations to automatically detect anomalies and focus their attention where it’s needed most. Our Splunk Al innovations provide domain-specific security and observability insights to accelerate detection, investigation and response while ensuring customers remain in control of how AI uses their data.”