Splunk has launched a groundbreaking GenAI summary tool on splunk.com and docs.splunk.com designed to provide users with an accelerated and accurate overview of the most significant information they require. This revolutionary feature offers contextual, high-level summaries extracted from a diverse range of relevant search results, covering everything from the usage of Splunk products and features to vital industry terms. Each search result is enhanced with descriptions generated by GenAI, providing a comprehensive summary of the referenced source. With this advanced search capability, Splunk users can now access the information they need more quickly than ever before.

Why is This Feature Essential?

As Splunk has grown, so has its digital footprint, boasting around 260,000 community members contributing over 147,000 posts. And that’s just one of our treasure troves of data! When you add product documentation, Knowledge Base articles, Splunk Blogs, and our developer portal into the mix, navigating the vast sea of resources can become quite daunting.

This enhanced experience seeks to save both time and effort by creating a centralized hub where users can investigate Splunk-related terms across various data sources, while also receiving comprehensive content summaries at both a high-level and document-specific view. The GenAI feature allows us to tap into our extensive knowledge base by training our Large Language Model (LLM) with a wealth of Splunk documentation—a depth of information that many other solutions simply do not possess.

Sources of Data

Our LLM is expertly trained on Splunk’s public documentation to eliminate irrelevant distractions that may arise from broader web content. The documents utilized for LLM updates are refreshed daily, ensuring you always have access to the newest information. The initial data sources include:

• Blogs: A wide array of articles discussing new product announcements and insights on building a resilient digital future.
• Community: A vibrant platform teeming with resources enabling Splunk users to ask questions, share experiences, and drive their organizations toward success.
• .conf: A trove of knowledge gathered during Splunk’s annual conference.
• Developer Portal: A comprehensive resource of official information to assist you in discovering and deploying Splunk software efficiently.
• Product Documentation: Each product in our portfolio is accompanied by detailed guides, including installation instructions, usage tips, release notes, and more, tailored to administrators, analysts, end-users, and developers alike.
• Lantern: This tool provides user-friendly Getting Started Guides and expert recommendations to make navigating Splunk a breeze, along with a library of procedural articles for tackling complex data challenges.
• Splunk.com: A broad overview of our products, solutions, resources, and company information.
• Knowledge Base Articles: An up-to-date collection of articles aimed at addressing specific queries without the need to contact Splunk support.

Features of the GenAI Summary Tool

The GenAI summary feature presents:

• High-Level Summary: This allows users to access key information from each relevant document, helping them understand essential details without sifting through multiple document links.
• Document-Level Summary: These summaries assist users in comprehending the contents of each search result, allowing them to avoid unnecessary document review.

Users can perform precise searches by product, feature, or broadly inquire about how to get started with Splunk. For example, in the screenshot below, a user explores the AI Assistant for the SPL app within specific product parameters.

Behind the Technology: LLM and Splunk AI Platform

This service is built on an open-source Large Language Model (LLM) integrated into the Splunk AI Platform. This platform also powers some of our most advanced AI Assistants, such as the AI Assistant for SPL. We maintain flexibility in response to marketplace innovations, with our infrastructure designed for straightforward model transitions when superior options become available. However, as is common with many GenAI applications, our LLM may sometimes produce hallucinations, and we recommend users verify their findings against the original data sources.

Enhanced Retrieval with RAG

Our LLM utilizes a Retrieval Augmented Generation (RAG) strategy to improve its performance. A diverse array of data is indexed in a vector database, ensuring that whenever a user submits a query, our system can effectively interpret the intent, search for relevant documents, and rank them to deliver the most applicable results to the LLM.

Safety Precautions and Limitations

We have implemented a variety of safety measures to enhance the quality of the responses provided by our services. These include safeguards against prompt injections, profanity, gibberish, and personally identifiable information (PII). It’s crucial to recognize that, despite these precautions, inherent limitations exist with Large Language Models. They may inadvertently produce information that seems credible but lacks factual grounding. While our protective measures are robust, they are not infallible; ongoing monitoring and continual improvements are essential for reinforcing the reliability of our services.

Conclusion

With Splunk’s revamped search experience leveraging advanced GenAI technology, users can enjoy a more streamlined process with specialized information easily at their fingertips. Discover this revolutionary feature today at splunk.com and docs.splunk.com.