Decision model evaluators, OpenAI and Anthropic model updates, Trace retention visibility
Create decision model evaluators
Create decision model evaluators to classify and score large volumes of text faster and at a much lower cost than LLM-as-a-judge evaluators. This release includes support for TypeSafe Jev decision models. Learn moreOpenAI and Anthropic model updates
The following LLM models are now available in evaluators, Playgrounds, and prompts:-
OpenAI:
- GPT-6 Astra
- GPT-6 Luna
- GPT-6 Sol
- GPT-6.1 Sol
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Anthropic:
- Claude Fable 5.1
- Claude Haiku 5.5
- Claude Opus 5.5
- Claude Sonnet 5.5
- GPT-4.1 Nano
- GPT-4 Turbo
- GPT-4o (2024-05-13)
- GPT-o1
- GPT-o3
- GPT-o4 mini
Trace retention visibility
The Splunk Observability Cloud trace retention policy is now visible on the Tracing tab for an Agent Stream. Tracing data for Agent Observability (SaaS) is retained for 30 days by default. Learn more
AI Assistant support for Splunk Agent Observability, control evaluator access by project and role
AI Assistant support for Splunk Agent Observability
You can now ask the Splunk Observability Cloud AI Assistant about Splunk Agent Observability features.Use the AI Assistant to troubleshoot your agentic system with questions like “Why did the agent take this action?” or “What’s driving this evaluator?” and it answers with links straight to the evidence and a concrete fix, pulling from your traces, spans, sessions, and evaluation scores. Learn moreControl evaluator access by project and role
Choose whether an evaluator is global and available in every project, or project-scoped and available in selected projects. A user’s project role determines their access to project-scoped evaluators. Learn moreLuna-3
Announcing Luna-3 for enterprise customers
Luna-3 is now available for enterprise users in realms us0, us1, eu0, and au0.Luna-3 is the third generation of Splunk Agent Observability evaluation models. It provides the following improvements over the previous generation:- Improved speed and accuracy: Luna-3 is 30-40% faster and improves accuracy by 8-10% for Prompt Injection, Toxicity, Sexism, PII, and Context Adherence evaluations.
- Multimodal evaluation: Use images as inputs with supported Luna-3 evaluators.
- Better generalization: Broader and more diverse training data improves performance across domains, writing styles, and applications.
- Greater prompt steerability: More detailed training labels help Luna-3 respond more effectively to evaluator instructions and policy boundaries.
- Shared semantics with LLM-as-a-judge: Luna-3 and LLM-as-a-judge evaluators now use the same logical inputs across sessions, traces, spans, and other supported evaluation levels.
- More efficient inference: A new sparse model architecture and vLLM-based serving improve performance and support quantized models.
- Prompt Injection
- Toxicity
- Sexism
- PII
- Context Adherence
Agent Observability for Splunk Observability Cloud, Tokenomics, Agent Observability in Cisco Cloud Cloud
Announcing Agent Observability for Splunk Observability Cloud
Splunk Agent Observability is the leading observability, evaluation, and guardrail platform for GenAI and agentic applications. Designed to empower engineers, product managers, and subject matter experts to build safe and reliable AI applications, Splunk Agent Observability works with all major LLM providers and can be used with your favorite agentic framework, a Python SDK, or an API.
Announcing Tokenomics in Splunk Agent Observability
Monitor AI tool cost and adoption across your organization with Tokenomics. This feature brings usage data from supported AI third-party providers into Splunk Agent Observability so you can understand cost, adoption, and the teams behind them.Use Tokenomics to track active users and usage trends over time to see which tools your teams use most. Drill down from organization-level totals to providers, models, job families, managers, and individual users. Learn more
Announcing Agent Observability in Cisco Cloud Control
Cisco and Splunk Observability Cloud customers can access a new Agent Observability app through Cisco Cloud Control, a unified platform for agentic operations with one login for every Cisco product.This integration helps teams connect AI infrastructure health with agent and model behavior, security, reliability, and cost efficiency. Learn more