AI Agent Monitoring Tools
AI agent monitoring tools watch your agent for your team. None of them prove it to your customer
AI agent monitoring tools like Langfuse, Galileo, Fiddler, Helicone, and Splunk trace what an agent did, track its latency and token cost, and run guardrails on every production interaction, so your own engineers see a broken agent before a customer does. That is a real job, and none of the five do a second job a B2B2C AI SaaS product also needs: showing the agent's proven value, deflection rate, cost per resolution, resolution rate, to the builder's own paying customers, scoped so one customer never sees another customer's numbers. This page covers what each tool actually does, what each one costs, and the specific gap a customer-facing product runs into once monitoring is in place and the agent is live.
The baseline
What AI agent monitoring tools actually watch
An AI agent monitoring tool watches a live agent while real traffic runs through it, not before release like an evaluation suite, but continuously after. It traces a request from the moment a user's message arrives to the moment the agent's response goes out, mapping every tool call and reasoning step in between, so an engineer can see exactly where a slow or wrong answer broke down. Alongside the trace itself, it tracks latency per step, GPU and memory use across the models and vector databases involved, and token cost broken down by request, model, agent, and workflow, so a team can tell which part of the system is expensive before the bill arrives. Most of the mature tools also run evaluations and guardrails on every live interaction rather than only on a fixed test set, catching a hallucination, a jailbreak attempt, or a policy violation as it happens instead of after a customer complains.
The tools that come up first for anyone researching this space split into a few real camps. Langfuse is open source and SDK-first, tracing agents and chats directly through Python or JavaScript with OpenTelemetry support for everything else, free up to fifty thousand units a month before any paid tier applies. Galileo and Fiddler both lean toward evaluation plus guardrails, scoring an agent's output for hallucination, toxicity, and policy risk in real time, Fiddler's guardrails free tier running under eighty milliseconds of added latency per check. Helicone sits closer to a lightweight proxy, a one-line integration that logs every request, session, and cost without asking a team to change how the agent calls its model. Splunk takes the opposite entry point entirely, an enterprise observability platform extending its existing infrastructure monitoring to cover GPU, memory, latency, and token cost across an agent stack, aimed at a team that already runs Splunk for everything else.
The five tools
Five monitoring tools, and what each one actually watches
Verified against each vendor's own pricing page. Real numbers, not list prices someone forgot to update.
Langfuse
Open source, SDK-first tracing for agents and chats, free for fifty thousand units a month. Core starts at $29 a month for a hundred thousand units, Pro at $199, Enterprise at $2,499 with an uptime SLA.
Galileo
Real-time evaluation and guardrails scored against hallucination and policy risk. Free for five thousand traces a month, then $100 a month for fifty thousand traces on the Pro plan, billed yearly.
Fiddler
Real-time guardrails against hallucination, toxicity, and prompt injection, free of charge and under eighty milliseconds of added latency. The Developer tier for deeper observability runs $0.002 per trace.
Helicone
A one-line proxy that logs every request, session, and cost. Free for ten thousand requests a month, $79 a month for Pro with unlimited seats and alerts, $799 for Team with SOC-2 and HIPAA compliance.
Splunk Agent Observability
Enterprise observability extended to trace agent workflows, GPU and memory use, and token cost by model and agent. A free edition covers up to fifteen hosts; beyond that, pricing is quote-based.
What none of the five answer
The one number none of the five ever scope to your customer
Every one of the five tools above answers a version of the same question: is the agent behaving correctly and efficiently, right now, for the team that built it. Langfuse's dashboards, Galileo and Fiddler's guardrail scores, Helicone's request logs, and Splunk's infrastructure charts all render inside a workspace scoped to your own account, read by your own engineers. None of them answer the question your own customer actually asks once the agent is live and the invoice shows up: is this thing working, and what did it save me. A trace tells you a tool call succeeded. It says nothing about deflection rate, the share of conversations the agent resolved without a human, and nothing about cost per resolution scoped to one specific customer's own traffic.
Langfuse comes closest to a version of this with its own multi-tenancy: unlimited projects, organization-level role-based access control on every plan, project-level access from Pro upward. That is still built for your own team members to manage many internal projects, not for your paying customers to see their own numbers. None of the five give a customer a scoped view of anything, because none of them were built with a second tenant layer in mind at all, your own customers, each needing a deflection rate and cost figure isolated so tightly that one customer's view can never leak a number belonging to a different customer on the same account.
The fix is not to drop monitoring, and it is not to stretch a monitoring tool into a job it was never built for either. It is to run both: a monitoring tool for what is happening right now inside the agent, and an embeddable, multi-tenant analytics layer for what that activity is worth to the person paying for it, deflection rate, cost per resolution, and resolution rate shown through white-labeled dashboard components inside your own product instead of a shared login to someone else's tool. AiAgRe's Node SDK reads the same underlying agent traces a monitoring tool would use, tags each event with both an org identity and a customer identity at ingestion, and turns that into per-tenant numbers a customer sees inside your product, not a separately branded vendor portal.
When one tool stops being enough
Three signs your monitoring tool alone won't cover what you need next
None of these show up in a trace or an alert. All three show up once real customers start asking questions.
Your customers ask what a session cost them, not what your P95 latency is
A customer renewing a contract wants their own deflection rate and cost per resolution, scoped to their own traffic, not a walkthrough of your Langfuse or Splunk dashboard scoped to an account they can't log into. A clean trace reassures your engineers; it does nothing to reassure the person deciding whether to renew.
One account, five tools, zero tenants
Every monitoring tool above scores your agent once, for your account, the same way evaluation tools do. None were built to isolate a result per customer the way tenant-scoped analytics has to, so a healthy average can hide one specific customer's real traffic quietly underperforming it.
Monitoring watches the agent. Nothing watches what it is worth
Every tool above traces latency, cost, and correctness. None of them turn that trace into a number your own customer would recognize as their return on what they are paying you, the same gap production observability practices leave open once you ask who the dashboard is actually for.
Pricing on the rest of the category
Verified pricing on the other tools teams shortlist alongside these five
The five above aren't the whole category. If your shortlist also includes Langfuse's full tier breakdown, Helicone's full tier breakdown, Braintrust pricing, Datadog LLM Observability pricing, Arize pricing, Portkey pricing, Galileo AI pricing, or Honeycomb pricing, each of those pages verifies the current published tiers line by line, the same way this one does for Langfuse, Galileo, Fiddler, Helicone, and Splunk. None of them add the customer-facing layer either; the gap above holds across the whole category, not just these five.
FAQs
AI agent monitoring tools: frequently asked questions
Common questions from teams comparing monitoring tools before they pick one, or before they realize they need a second layer on top.
What do AI agent monitoring tools actually monitor?
An AI agent monitoring tool traces a live agent's requests from the moment a message arrives to the moment a response goes out, mapping every tool call and reasoning step along the way. Alongside the trace, it tracks latency per step, GPU and memory use across the models and vector databases involved, and token cost broken down by request, model, agent, and workflow. The more mature tools also run evaluations and guardrails against every live interaction, not just a fixed test set, catching a hallucination or a policy violation as it happens instead of after a customer complains.
Which AI agent monitoring tool should I pick?
Pick Langfuse if your team wants open source, SDK-first tracing with room to self-host later. Pick Galileo or Fiddler if guardrails and real-time evaluation against hallucination and policy risk matter more than raw tracing depth, Fiddler in particular if you want that scoring free and under eighty milliseconds of latency. Pick Helicone if you want a one-line proxy that logs everything without touching how your agent calls its model. Pick Splunk if you already run Splunk for the rest of your infrastructure and want agent monitoring inside the same platform instead of a separate bill. None of the five rule out the others, and teams that need both tracing depth and enterprise infrastructure monitoring often run two.
Are AI agent monitoring tools free?
Langfuse's Hobby plan is free for fifty thousand units a month, with Core starting at $29 a month once you outgrow it, Pro at $199, and Enterprise at $2,499 with an uptime SLA. Galileo is free for five thousand traces a month, then $100 a month for the Pro plan's fifty thousand traces, billed yearly. Fiddler's real-time guardrails are free with no cost per check; its Developer tier for deeper observability runs $0.002 per trace. Helicone is free for ten thousand requests a month, then $79 a month for Pro and $799 for Team with SOC-2 and HIPAA compliance. Splunk offers a free edition covering up to fifteen hosts, with pricing beyond that available only by contacting sales. All figures are each vendor's own published pricing, current as of this page's publish date, and worth reconfirming before you budget against them since usage-based add-ons change the real bill fast.
Can AI agent monitoring tools show data to my own customers?
No, and that is by design, not an oversight. Every one of the five tools above renders its results in a workspace built for your own engineers, scoped to your account, with no notion of your own paying customers as a separate audience. If you sell an AI agent inside a product other companies pay for, your customers want their own deflection rate, cost per resolution, and resolution rate, scoped to only their own data, which is a different job than watching for a slow trace or a failed guardrail check. AiAgRe's embeddable dashboard components exist for exactly that second job, and most teams run one alongside the other rather than trying to make one tool do both.
What's the difference between AI agent monitoring and AI agent observability?
The two terms mostly describe the same practice from different angles. Observability usually refers to the underlying data, the traces, logs, and metrics an agent emits, and the ability to ask new questions of that data without shipping new code. Monitoring usually refers to what a team actually does with that data day to day, watching dashboards, setting alert thresholds, and getting paged when a metric crosses one. Read more in the guide to AI agent observability for the deeper distinction and what to trace in the first place.
Can I use more than one monitoring tool at once?
Yes, and plenty of teams do, usually because different tools are strong at different layers. An open source tracer like Langfuse stays attached to every agent call for debugging, while a guardrails-first tool like Fiddler or Galileo screens each response for hallucination or policy risk before it ever reaches the user, and an enterprise platform like Splunk rolls agent metrics into the same infrastructure dashboards a platform team already watches. Running two or three of these rarely causes conflict, since each one reads the same underlying trace data through a different lens.
Picked a monitoring tool? Now prove it to your customers.
Request access and we'll walk through how AiAgRe's embed tokens map onto the traces your monitoring tool already reads.