Learn how to use Splunk to monitor the security of local Large Language Models (LLMs) like Llama and GPT4ALL.

Discover how Graph Neural Networks (GNNs) enhance security and observability within Splunk. Learn to detect anomalies, predict threats, and optimize system performance using GNNs. Explore the power of graph analytics in your Splunk environment.

In this blog, we explore the potential of utilizing Splunk SOAR for agentic AI workflow design and execution based on LLM-RAG functionalities from Splunk App for Data Science and Deep Learning (DSDL).

Simplify fraud investigations with AI & Splunk.

Splunkers Mohit Verma and Jeff Wiedemann break down the latest advancements in Splunk AI Assistant for SPL v1.1, featuring personalized SPL queries, enhanced AI capabilities, and categorized prompt suggestions.

Discover how Splunk’s AI Assistant transforms observability with AI-driven insights. Learn 7 powerful use cases to enhance performance and incident response.

With rapid advancements in AI, digital resilience is no longer optional – that's why leading organizations trust Splunk’s unified security and observability platform to keep their digital systems secure and reliable.

In this version 5.2 release of Splunk DSDL, we introduce new functionalities utilizing retrieval-augmented generation with local large language models and a vector database. In this blog, we provide an overview of various use cases supported through a set of DSDL commands and dashboards.

Who doesn’t love a bit of anomaly detection with Splunk? As someone who has spent far too long talking about cyclical statistical forecasts and anomalies, you’ll be relieved that this is a topic that we don’t get tired of here at Splunk! In this blog post we will be taking you through some of the recent changes to the Machine Learning Toolkit, where we have released a more scalable version of our users most favorite algorithm.