Splunk Blogs

Understand the tradeoffs between LLMs and humans for generative AI evaluation

LLM judge vs SLM judge: an SLM costs 10-30x less and runs in 15-150ms, making 100% coverage affordable. See where each wins and when to make the switch.

Evaluate multi-agent AI systems using benchmarks that prioritize coordination, reliability, and policy adherence over simple accuracy scores to ensure production readiness.

How to build an SLM judge: See how to size the model, fine-tune with LoRA, validate it, and serve it in production.

The conversation is shifting from AIOps to Agentic Ops.

Learn how to implement an end-to-end enterprise RAG architecture, step by step through the pipeline, by understanding common failures.

Observability Studio lets developers test and validate tracking data in real time during development, catching problems before they reach production.

Discover how security leaders use AI coding assistants and tiered sandboxes to empower frontline analysts to prototype faster without production risk.

Evaluate the effectiveness of AI agent self-reflection to determine when internal revision passes actually improve accuracy versus when they introduce new errors.