Helicone Alternatives in 2026: A Migration Guide

If you run Helicone in production, you need a plan. In March 2026 Helicone was acquired by Mintlify and moved to maintenance mode: it still receives security patches and bug fixes, but active feature development has stopped, new signups are disabled, and existing customers are being pointed toward other tools. The short answer to "what should I move to": if you mainly logged raw LLM requests, an open-source tracer like Langfuse is the closest like-for-like; if you run agents, multi-step chains, or n8n workflows and care about cost and reliability — not just request logs — a production AI-operations platform like Obsivara is the better fit. The rest of this guide covers every serious option and how to migrate without losing data continuity.

What actually happened to Helicone

Helicone earned its popularity on one thing: the fastest possible setup. Route your LLM traffic through its gateway — or change a single header — and you immediately got request logs, latency, caching, and per-request cost tracking. That proxy-first model made it a default choice for teams that wanted visibility in an afternoon.

After the Mintlify acquisition in March 2026, that trajectory changed. Maintenance mode means the product is kept running and secure, but it is no longer being built on: no new integrations, no new models added on a roadmap, and no new accounts. For a fast-moving space like LLM observability — where new providers, agent frameworks, and pricing models appear monthly — a frozen product ages quickly. That is why the practical move for most teams is to migrate now, on your own timeline, rather than under pressure later.

What to look for in a replacement

Before you pick a tool, decide what you actually need — the answer determines which alternative fits. Three questions matter most.

First, ingestion model: Helicone's proxy sits in your request path. Some alternatives keep that gateway style; others observe from outside via an SDK, OpenTelemetry (OTLP), or webhooks, so nothing new sits between you and your model provider. Second, scope: are you logging individual LLM requests, or do you need to see whole agents, tools, and multi-step workflows end to end? Third, what you do with the data: raw traces and dashboards, or higher-level operations — cost attribution by model and workflow, health scoring, and alerts that fire before an incident. A tool that's great at one of these is often only adequate at the others.

The best Helicone alternatives in 2026

No single tool replaces Helicone for everyone, because "observability" means different things to a proxy user, an agent builder, and an ops team. Here is an honest map of the strongest options and who each suits best.

Langfuse — the closest open-source like-for-like

If what you valued in Helicone was open, self-hostable request logging, Langfuse is the most direct replacement. It's an open-source (MIT) platform for LLM tracing, prompt versioning, and evaluations, and it can be self-hosted for full data control. Langfuse was acquired by ClickHouse in January 2026 but remains open-source and self-hostable, with its cloud offering continuing. The trade-off versus Helicone: Langfuse is SDK/OpenTelemetry-based rather than a drop-in proxy, so migration means adding instrumentation rather than flipping a header.

LangSmith, Arize Phoenix & Braintrust — specialist fits

LangSmith is the strongest choice if your stack is built on LangChain or LangGraph — its tracing and evals are native to that ecosystem, though it's closed-source and most valuable inside it. Arize Phoenix is open-source and excellent for LLM and RAG evaluation and experimentation, typically in notebooks and development rather than as a production ops layer. Braintrust centers on eval-driven development and prompt experimentation. All three are good tools; none of them is aimed squarely at the thing Helicone did — cheap, broad production visibility — which is why teams that used Helicone for operations rather than experimentation often land elsewhere.

Where Obsivara fits

Obsivara is built for the case Helicone users hit as they scale: you no longer just have LLM requests, you have agents, tools, and workflows, and you need to know what they cost and whether they're healthy — not just read their logs. It ingests via SDK, OpenTelemetry, webhooks, or native n8n (no proxy in your request path), then layers cost intelligence by model/agent/workflow, health scoring, a dependency knowledge map, and predictive failure alerts on top of tracing. If you orchestrate with n8n in particular, the complete guide to monitoring n8n workflows shows what that native coverage looks like.

The honest boundary: if all you ever needed was one-line per-request logging and you're happy staying on a maintenance-mode product for now, you may not need to move yet. If you want an actively developed platform that treats production reliability and cost as first-class, see the full Obsivara vs Helicone comparison, or start with a free 48-hour audit that shows your real cost and failure rate before you commit.

How to migrate off Helicone without losing continuity

A clean migration is four steps. One — inventory what Helicone gives you today: which apps route through it, what you rely on (request logs, cost, caching, alerts), and what data you need to retain. Export or archive the historical logs you care about before you cut over, since a maintenance-mode product is not where you want your only copy of last quarter's cost data.

Two — pick the replacement using the three questions above, and choose its ingestion path (proxy-style, SDK, OTLP, or webhook). Three — dual-run: send data to both Helicone and the new tool for one to two weeks so you can confirm parity on the metrics you actually use before trusting the new one. Four — cut over: move traffic off the Helicone proxy (or remove its header), verify your dashboards and alerts fire on the new platform, and decommission the Helicone integration. Dual-running is the step teams skip and regret; it's what turns a migration from a leap into a controlled switch.