Your agents ran thousands of times last month.
You got back one number.

Agents call models, use tools, retry, loop and make decisions, thousands of times a day, and the only thing that reports back is a monthly invoice. AgentPing gives you the run behind every dollar.

Try it live in 30 seconds Track your first AI workflow
Free plan, no card required Works with any AI workflow Live in minutes

AgentPing helps you answer these three questions

Most teams cannot, until the invoice arrives. A 42% jump is one customer at ten times their usual volume, or a prompt change that doubled context, or a quiet switch to a pricier model, or a retry loop with no cap. Four different answers. One number.

AgentPing gives you the answer, run by run.

01

Spend

Know which customer and feature caused the bill.

→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

Know whether your agents actually ran.

→Get alerted when scheduled workflows fail, stall, miss a run or go silent. A silent agent is the only failure with no upper bound on how long it can last.

Explore Pulse →

03

Verify

Know when successful runs are no longer good enough.

→Track quality signals, evals and drift so "200 OK" does not hide bad answers after a provider-side model change.

Explore Verify →

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

AgentPing sits beside your existing stack and gives production AI workflows the context traditional tools were not built for. See the difference in 30 seconds, no signup →

Start with one agent.

No platform rollout. Track one workflow, see what it cost and whether it behaved, and decide from there.

01

Create a project

One account, your first project, in under a minute.

02

Add one agent

Name the agent or workflow you want to watch first.

03

Send a run event

By SDK or a single webhook. Two lines of code or one HTTP request.

04

See the run

Cost, status, model and latency, live in the dashboard.

05

Add an alert

For cost spikes or missed runs, to a channel you watch.

Send a test run now, no signup Track your first AI workflow

Built for all types of teams.

By industry Customer support Sales & RevOps E-commerce & retail Legal & professional services

Works with the stack your agents already use.

Send events from LangChain, the OpenAI Agents SDK, the Vercel AI SDK, n8n, Laravel, GitHub Actions, scheduled jobs or any workflow that can call a webhook.

View integrations → It works with curl, so it works with anything. Prove it in 30 seconds →

Monitor production AI without exposing more than you need to.

Start with metadata such as agent name, run status, model, token usage, cost, latency and your own customer or feature identifiers. Sensitive prompts and outputs are optional, configurable and clearly explained, so you can get cost and reliability visibility without sending content you would rather keep.

Read about data and security → Your data →

Frequently asked questions

What is AI agent observability?

It is monitoring AI agents the way you monitor production systems: what each agent run costs, whether scheduled runs actually fired, and whether output quality is holding up. AgentPing puts cost attribution, uptime and quality scoring on one event, the agent run, rather than scattering them across separate tools.

How is AgentPing different from Sentry or Datadog?

Sentry and Datadog watch infrastructure and exceptions; they do not know what an agent run cost, whether a scheduled agent missed its window, or whether a 200 OK hid a bad answer. AgentPing is built around the agent run, so cost per customer, schedule freshness and output quality roll up to the agent, not the host.

How does the price compare to my LLM bill?

Most teams find AgentPing costs 1 to 3% of their monthly LLM spend. A team spending $15,000 a month typically lands on the Team plan at $199, about 1.3% of the bill. The first cost spike it catches usually pays for the next year of subscription.

Will it slow my agents down?

No. The SDK never blocks your agent. Telemetry runs on a separate thread with a hard 2-second timeout, a bounded local queue, and graceful degradation when our service is unreachable. If we go down, your agents run as if we weren't installed.

What's the deployment model?

Fully hosted SaaS. You pick the ingestion region: US or EU.

Can I export my data?

Yes. Full event export to JSON or Parquet. API access on every tier. We don't lock your data in.

Start monitoring your first production AI workflow.

Send a test run from your terminal right now and watch it land, cost and all. Then wire up a real agent. 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.