000 compare

AgentPing vs Helicone.

Both tools track LLM usage and surface cost. The architectural choice is the difference: Helicone is a proxy that intercepts API calls; AgentPing is an SDK that wraps the agent run. The proxy sees calls; the SDK sees agents. This page walks through what each one is built for.

001 what helicone does well

Easy proxy integration, cost dashboards, an open-source option.

Helicone's proxy model means integration is a URL swap. If you already have a single shared OpenAI or Anthropic client and you want a cost-and-latency dashboard without writing SDK glue, Helicone is the path of least resistance. The open-source option is also genuinely useful for teams with data-residency constraints.

002 where agentping differs

Watches the agent, not just the API call. Three pillars on one event.

AgentPing's primitive is the agent run. One run may make zero LLM calls or many; the agent is still one record. From that record, cost attribution rolls up by agent / customer / feature. Schedule freshness fires when a scheduled run doesn't land. Quality scoring (deterministic checks plus LLM-as-judge with calibration anchors) catches drift before the customer does.

Side-by-side

capabilities honest read
Capability Helicone AgentPing
Integration model Proxy (URL swap) SDK (1-line init, non-blocking)
Unit of analysis API call Agent run
Cost attribution by customer / feature By user / property First-class, retroactive once tagged
Schedule freshness (missed cron alerts) Not a focus Per-agent cron + tolerance window
Quality scoring (deterministic + judge) Limited Two layers + drift detection on distribution
Anomaly detection on per-agent spend Not a focus 14-day baseline, alert routes per agent
Self-hosted / open-source option Yes Hosted SaaS only at launch
Network hop on hot path Yes (proxy) No (background thread)
003 when to pick which

Different shapes, different jobs.

Helicone is a great cost-and-latency proxy for teams that just need an LLM call dashboard. AgentPing is the right tool when "which agent caused this" and "is this agent still working" are the questions.

Pick Helicone if

  • You want a single proxy URL swap and a cost dashboard without an SDK in your code path.
  • You need a self-hosted / open-source option for data-residency reasons.
  • You operate one or two agents on one shared API key and don't need fine-grained per-agent attribution.

Pick AgentPing if

  • Agent identity matters: you need cost per agent, customer, and feature, not per key.
  • You run scheduled agents and need missed-run alerts within a grace window.
  • You want continuous quality scoring (deterministic checks + LLM-as-judge) on the production stream.
  • You'd rather not add a network proxy on the LLM hot path.
  • You want one tool for cost, monitoring, and quality with shared alert routing.
004 frequently asked
Helicone is a proxy. Does AgentPing work the same way?
No. AgentPing is SDK-based, not proxy-based. A proxy intercepts every LLM call by sitting in the network path; an SDK wraps the agent run and the LLM clients you already use. The SDK approach avoids adding a network hop in your hot path and works the same whether you call Anthropic, OpenAI, or self-hosted models. The trade-off is one line of SDK initialisation versus a proxy URL swap.
What does AgentPing capture that a proxy can't?
A proxy sees individual API calls but doesn't know which agent issued them or whether the agent run succeeded. AgentPing wraps the agent run as the unit of analysis, so cost attribution, schedule freshness, and quality scoring all roll up to the agent (and optionally the customer or feature). A run might issue zero, one, or fifty LLM calls; the agent is still one record.
Does Helicone do quality scoring?
Helicone has prompt versioning and basic eval surfaces, but live drift detection on the production score distribution is not its primary focus. AgentPing's Verify side runs deterministic checks plus LLM-as-judge with calibration anchors, with a hard per-team spend cap on the judge calls and statistical drift detection on the rolling baseline.
How does pricing compare?
Helicone has a free tier with paid usage scaling. AgentPing is flat-tier (Starter £99, Team £249, Business £499), with annual billing saving 20%. The flat tier is predictable; the usage tier suits bursty workloads. Pick based on volume and budget shape.
Can I use both?
Technically yes; in practice the SDK + dashboard overlap means most teams pick one. If you already have Helicone for the proxy and just need per-agent attribution plus schedule monitoring, AgentPing can run alongside without conflict; events flow independently.
005 read next

How AgentPing implements cost, monitoring, and quality.

Features → What is AI agent observability? → Docs →