What Helicone does well: drop-in observability at the LLM-call boundary — route requests through Helicone's proxy (or its async logging SDK) and get request/response logs, caching, rate limiting, and cost tracking, largely without touching your agent's own code. It's a lightweight, framework-agnostic way to see what's going to and coming back from the model.
What Dunetrace adds: a proxy sees individual LLM requests — it has no native concept of a multi-step agent run, a tool call, or a retrieval step, and can't see patterns that only emerge across several of them (the same tool called repeatedly, a retry storm, a goal abandoned after tool use stops). Dunetrace's SDK instruments the whole run — tool calls, retrieval, and LLM exchanges together — so its 23 structural detectors can catch failure patterns that live in the relationship between steps, not just in any single LLM call. That same run-level visibility is also what makes in-path runtime prevention possible.
Side by side
| Dunetrace | Helicone | |
|---|---|---|
| Unit of observation | The whole agent run — tool calls, retrieval, and LLM exchanges together | Individual LLM requests/responses through the proxy |
| Multi-step failure patterns (loops, retries, abandonment) | Yes — 23 structural detectors, purpose-built for this | Not visible at the proxy layer — no run-level state |
| Can stop a run mid-flight | Yes — runtime prevention policies | No — a proxy can rate-limit/cache a call, not reason about a multi-step run |
| Setup | SDK instrumentation (two lines) or auto-instrumentation | Route calls through the proxy or use the logging SDK |
| Per-call cost/caching | Cost tracked per run; no caching layer | Yes — this is a core strength |
| Proactive alerting | Slack / webhook / Linear, <15s, on structural patterns | Alerting exists at the request/cost level |
Use both
They operate at different layers and don't conflict — Helicone in front of your LLM calls for caching, rate limiting, and per-request cost visibility; Dunetrace instrumenting the agent run itself for structural failure detection and runtime prevention across the whole multi-step execution.