Your agents ran all day and night.
See what they got up to.

One record per run: what it cost, whether it ran on time and whether the output held up. Agent Ping pages you when a run breaks its pattern, and it takes one line to start.

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Free plan, no card required Works with any AI workflow Live in minutes

One command. Simple.

One line is the whole integration. Send it from anything that can make an HTTP request and the run lands with its cost, timing and owner. Or drop in the Python, TypeScript, Go or Laravel SDK and every OpenAI and Anthropic call is captured for you.

your terminalone line
curl 'https://eu.ingest.agentping.io/v1/ping?key=ping_eu_...&agent=nightly-report&status=ok&model=gpt-4o&input_tokens=1850&output_tokens=420'
OK
Runs · nightly-reportlive
AgentStatusCostModelWhen
nightly-reportok$0.0088gpt-4ojust now
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Observability for every single agent run.

Every run is recorded with what it cost, whether it ran on time and how good the output was. Three views, one record.

01

Spend

What did it cost, and which customer was it for?

→Every run carries the agent, customer, feature, provider and model behind it, so one total becomes unit cost per customer and cost per successful run. Baselines per agent page you when one drifts.

  • Cost per customer, so you can see who is unprofitable by name
  • Cost per feature, so a repricing decision has a number behind it
  • Anomaly alerts per agent, so a runaway loop is a page and not a month

Explore Spend →

02

Pulse

Did last night's run actually happen?

→Each agent learns its own schedule. When a run is late, stalls or never arrives, you get paged, instead of finding out from the silence.

Explore Pulse →

03

Verify

Was the answer it gave any good?

→Quality signals, evals and drift sit on the same run record, so you see a model change make answers worse the morning after, not the quarter after.

Explore Verify →

Start with one agent. Roll out from there.

Pick your most expensive agent first. Connecting it takes a few minutes, and adding the rest is the same two lines or one webhook each.

01

Get a key

Create a team and copy the key. Under a minute, free plan, no card.

02

Report a run

Drop the SDK into your code and every provider call is captured. No SDK? One webhook from cron, n8n or curl does it.

03

See it, then set an alert

Cost, status, model and latency land live. Add an alert for a cost spike or a missed run, to a channel you watch.

Read the quickstart → See what it plugs into →

Built for the teams running agents in production.

Your current tools only show part of the picture.

Current toolWhat it showsWhat is missing
OpenAI or Anthropic dashboardsTotal usage and spendCost by agent, customer, feature or run
Logs and SentryErrors and exceptionsMissed runs, AI cost context and quality signals
Cron monitorsWhether a scheduled job firedWhat the AI run cost, produced or retried
SpreadsheetsManual cost trackingReal time alerts and run level visibility

Try the playground →

Your logs watch the server. Agent Ping watches the run.

Traditional observability asks whether the service is up and how fast it answered. An agent can pass both and still have skipped last night's run, cost ten times normal or given a worse answer. Agent observability tracks the run itself: what it cost, whether it happened on schedule and whether the output was good.

Traditional observabilityAgent observability
Unit of measureRequest, host, exceptionOne agent run, end to end
What a failure looks likeA 500 or a stack traceA 200 OK that cost too much, arrived late or answered badly
CostInfrastructure, by hostTokens, by agent, customer and feature
ScheduleIs the service up?Did this agent run when it should have?
QualityNot measuredScored per run, with drift alerts

vs Datadog → vs LangSmith → vs Langfuse → vs Helicone → vs Braintrust → vs AgentOps →

Works with your stack, without taking your data.

Send events from LangChain, the OpenAI Agents SDK, the Vercel AI SDK, n8n, Laravel, GitHub Actions or anything that can call a webhook. You send metadata by default; prompts and outputs are opt-in, per agent. EU or US data region, your choice.

View integrations → Data and security →

Cheaper than a runaway agent.

Most teams add observability after the first surprising invoice. Put it in the day an agent goes to production instead and every run is attributed from the start, so a loop that would have run all weekend gets paged in the first hour. Agent Ping costs about 1 to 3% of your LLM bill. One caught spike usually covers the year.

See pricing → Estimate what your agents cost →

Start monitoring your first production AI workflow.

Connect your most expensive agent today. The first alert will tell you whether it was worth it. Free to start, live in minutes.

Try it live in 30 seconds Track your first AI workflow

See all features →

Free to start. No card. 14-day trial on paid plans. The SDK never blocks your agents, and never crashes them.