Loading tool details…
Complete pricing guide for Splunk AI Assistant & Observability. Compare all plans, analyze costs, and find the perfect tier for your needs.
Not sure if free is enough? See our Free vs Paid comparison →
Still deciding? Read our full verdict on whether Splunk AI Assistant & Observability is worth it →
month
500MB/day, testing only
month
Custom based on workloads
month
Based on daily ingestion
month
Host-based
Pricing sourced from Splunk AI Assistant & Observability · Confirm current pricing and terms with the vendor.
A check mark means listed in that plan’s record. A dash means not listed, rather than confirmed unavailable. Verify current vendor terms.
Splunk provides specialized monitoring for AI applications including LLM performance metrics, quality measures (hallucinations, bias, drift), token usage, and cost tracking. It traces dependencies across AI workflows and correlates technical performance with business impact.
When incidents occur, the AI agent automatically analyzes metrics, events, logs, and traces to generate evidence-based root cause summaries, assess business impact, and provide actionable remediation plans — eliminating manual correlation work.
Splunk's AI Agent Monitoring provides comprehensive LLM observability including prompt/completion tracking and token analytics. For enterprise deployments, it can serve as a unified platform, though specialized tools may still be useful for development workflows.
Splunk provides specialized monitoring for Cisco's pre-validated AI infrastructure solutions, tracking GPU utilization, tokenomics metrics (time-to-first token, costs), throughput, and resource efficiency across the AI lifecycle.
Splunk is typically 3-4x more expensive than alternatives due to per-GB pricing. Base pricing starts around $15,000/year for 5GB/day, with enterprise deployments often exceeding $500,000/year including add-ons and infrastructure.
AI builders and operators use Splunk AI Assistant & Observability to streamline their workflow.
Try Splunk AI Assistant & Observability Now →Datadog LLM Observability (part of Datadog's Agent Observability suite) is the enterprise APM's answer for AI agents and LLM apps: end-to-end tracing of prompts, tool calls, and retrieval steps; quality evaluations; cost tracking per model; and security detections — all inside the same UI where your infra, APM, and RUM traces already live.
Compare Pricing →Open-source LLM engineering platform that captures traces, runs evaluations, and helps teams analyze cost, latency, and quality across production AI apps.
Compare Pricing →Arize Phoenix is an open-source AI observability and evaluation platform for tracing, testing, and improving LLM applications and agents.
Compare Pricing →Sentry AI Monitoring is Sentry's AI and LLM observability capability for monitoring agent runs, LLM calls, model costs, token usage, errors, traces, and production performance inside the broader Sentry platform.
Compare Pricing →