Alternatives to Helicone

Helicone alternatives, and what maintenance mode means

Helicone is Apache-2.0 with no enterprise directory, and Mintlify acquired it in posts dated 3 March 2026. Both companies say it now runs in maintenance mode, which they define as security updates, bug fixes and new models continuing to ship. That constrains new feature work rather than ending the product, and it is worth weighing alongside the narrower reasons teams look elsewhere.

Reviewed 31 August 2026. Licences read from each project's LICENSE file, stars and commit activity from the GitHub API, datastore lists from each project's docker-compose, prices from each vendor's own pricing page, and Helicone's status from Helicone's and Mintlify's own acquisition posts dated 3 March 2026.

Why teams look for an alternative

Maintenance mode, in the company's own words
Mintlify acquired Helicone in posts dated 3 March 2026. Helicone's says its services will remain live for the foreseeable future in maintenance mode, and both companies define that as security updates, bug fixes and new models continuing to ship. Commit volume agrees: 37 to 76 a month in the four months before, 1 to 6 a month since April 2026. The README mentions none of it.
Supported on-prem sits on the Enterprise tier
The Apache-2.0 code is available to run, but the supported on-prem path is a sales conversation. If you want a vendor relationship for a self-hosted deployment, that is a tier decision.
Compliance coverage is priced at $799 per month
SOC 2 and HIPAA sit on the Team tier. For a small team that is a large step from Pro at $79.
You need scope past observability
Agent execution, isolated sandboxes and evaluation workflows are outside its scope.

The alternatives

Langfuse

The best-known open source LLM observability platform, now owned by ClickHouse.

  • MIT core plus a separate enterprise licence over ee/, web/src/ee/ and worker/src/ee/
  • 33,900+ GitHub stars, acquired by ClickHouse in January 2026
  • Hobby free with 50,000 units/month, Core $29, Pro $199, Enterprise $2,499/month
  • Mature prompt management and a well documented OpenTelemetry path

Best for: Teams who want the largest community, the most integrations and the most mature prompt tooling.

Watch out: Nine features need a licence key when self-hosting, including audit logs, data retention policies and server-side data masking. Those are exactly what a regulated team self-hosts for.

Full Langfuse comparison

Opik

Comet ML's observability and evaluation platform, with the largest community of the clean-licence options.

  • Apache-2.0 with no enterprise directory, 21,697 GitHub stars (August 2026)
  • Self-hosted build has all features except user management
  • Free Cloud at $0, Pro Cloud $19/month, Enterprise custom
  • First-party OpenTelemetry support

Best for: Teams who want a complete self-hosted build with a genuinely clean licence and a large community behind it.

Watch out: Five datastores to operate: MySQL, Redis, ClickHouse, Zookeeper and MinIO. Whether it maps gen_ai.* semantic conventions or a proprietary schema was not something we could confirm from its docs.

OpenLIT

The lightest option here: SDK to OpenTelemetry Collector to ClickHouse, and nothing else.

  • Apache-2.0, 2,731 GitHub stars (August 2026)
  • One datastore
  • No paid tier exists today
  • Maintains the gen_ai semantic conventions with the OpenTelemetry community

Best for: Teams optimising for the least infrastructure to operate, who will self-host permanently.

Watch out: No managed cloud. OpenLIT Cloud is listed as coming soon with no pricing, so there is nowhere to go if you later need a hosted product with an SLA.

Laminar

An Apache-2.0 platform where the cloud and self-hosted builds have feature parity.

  • Apache-2.0 (in LICENSE.md rather than LICENSE), 3,212 GitHub stars (August 2026)
  • PostgreSQL, ClickHouse and Quickwit: three datastores
  • Free $0 with 1 GB, Starter $30, Pro $150/month, Enterprise custom
  • Accepts OTLP over gRPC, HTTP protobuf and HTTP JSON

Best for: Teams who want the option to move between cloud and self-hosted without losing features.

Watch out: The smallest community here, and a recent rebrand has left some redirecting documentation URLs.

OpenLLMetry

Instrumentation rather than a platform: it produces spans and sends them to a backend you already run.

  • Apache-2.0, 7,409 GitHub stars (August 2026)
  • Its semantic conventions became the basis for OpenTelemetry's official GenAI effort
  • Exports to Traceloop or 30+ external backends including Datadog, Grafana and Honeycomb
  • Traceloop platform: free tier with 24 hour retention, then Enterprise

Best for: Teams who already operate an observability stack and would rather have LLM spans inside it than beside it.

Watch out: It is not a backend. You still need somewhere for the spans to land. Traceloop's free tier retains data for 24 hours, which is a demo rather than a production tier.

Everstack

Observability that arrives as a side effect of routing, on a control plane that also runs agents and sandboxes.

  • Apache-2.0 across the repository, no enterprise directory
  • Self-hosting is the default at any tier
  • Traces exist without instrumenting each service, because requests pass through the gateway
  • Starter $0, Build $20/month, Scale $100/month (August 2026)

Best for: Teams with services in several languages, or integrations they cannot instrument, where per-service rollout is the thing blocking coverage.

Watch out: A much smaller community than Langfuse or Opik, and a younger trace UI. If observability is your only problem, the focused tools are more polished.

How to choose

  1. 01

    Does the licence gate what you self-host for?

    If you are self-hosting because of audit logs, retention policy or data masking, Langfuse's ee/ carve-out means a licence key. Opik gates only user management. OpenLIT, Laminar and Everstack gate nothing.

  2. 02

    How many datastores can you actually operate?

    One (OpenLIT), three (Laminar), or five (Opik) are very different commitments at 3am. Nobody regrets the lighter stack until they need something it does not do.

  3. 03

    Do you already have an observability backend?

    If yes, look hard at OpenLLMetry before standing up a second platform. A separate LLM observability tool means a second place to look during an incident.

  4. 04

    Where do traces come from?

    Instrumentation is a code change in every service you want covered, and it is the step that decays as new services ship. Gateway-level traces cost nothing per service but only see the request boundary. Most teams end up wanting both.

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