Langtrace Review (2026)

What Langtrace is

Langtrace is an open-source, OpenTelemetry-based observability tool for LLM applications. It captures, debugs and analyses traces and metrics from applications that use LLM APIs, vector databases and LLM frameworks, with SDKs for Python and TypeScript.

The distinguishing technical choice is that it is OpenTelemetry-native rather than OpenTelemetry-compatible. A lot of tools in this category built a proprietary trace model first and bolted OTel on afterwards as an ingest path. Langtrace started from OTel. In practice that means your trace data is genuinely portable - the spans it emits are standard spans, and you are not locked into a vendor-specific representation.

The second thing it does better than most: it traces vector database operations as first-class spans. Pinecone, Chroma, Weaviate and others show up in the trace alongside the LLM calls.

That sounds like a minor feature. For RAG applications it is not. A large share of RAG failures are retrieval failures - the model answered badly because it was handed the wrong chunks - and most observability tools show you the bad answer while leaving retrieval as an opaque gap. Seeing the query, the returned chunks and the generation in one trace is the difference between debugging RAG and guessing at it.

The license split, and why it matters

This is the detail most comparison pages get wrong, because they report a single license for the project.

There are two:

Component	License	What it means for you
SDKs (Python, TypeScript)	Apache 2.0	Instrument your app freely. No obligations.
Application / server	AGPL-3.0	Copyleft. Modify and offer over a network, and you must offer your source.

For a team self-hosting Langtrace unmodified for internal use, the AGPL is a non-issue and you should not let it scare you off.

For a team that wants to fork it, embed it in a commercial product, or offer a hosted version to customers, the obligations are real and you should get legal review before writing code against it. AGPL’s network clause is specifically designed to close the “we only offer it as a service” gap that GPL leaves open.

This is a genuine differentiator against Langfuse (MIT) and Opik (Apache 2.0), both of which are permissive. If your legal team has a blanket policy against AGPL - and many do - that decision is made for you regardless of the product’s merits.

The commercial question

Here is the thing nobody writes down, and it is more important than any feature comparison on this page.

Langtrace cloud is free because it has never been monetised. The vendor’s own FAQ states plainly that it is not currently charging for the cloud, that it is primarily looking for feedback, and that it will inform users when it decides to monetise.

That is admirably honest. It is also an explicit announcement that pricing is coming at an unspecified date.

Set that alongside the funding picture. Public data shows Scale3 Labs, founded in 2022 in San Francisco, at seed stage with roughly $5.3M raised, last raised around 2022. For a company that is not charging for its product, a four-year-old seed round is a long time.

We want to be careful here. This is not a prediction of failure, we have no inside information, and the product is actively developed and promoted. But if you are choosing an observability platform, the honest framing is: the free cloud is not a stable planning assumption. Use it happily for evaluation and side projects. If it becomes load-bearing in production, have your self-hosting path tested and ready, because the self-hosted build is genuinely free and that is your insurance.

A note on a bad signal we chased

While researching this page we hit search results whose title suggested Scale3 Labs had sunset. We chased it specifically, because a dead vendor changes the recommendation completely.

It appears to be stale or wrong. The vendor’s own site actively promotes Langtrace as a current product, describes it as open-source tracing and monitoring with OpenTelemetry support out of the box, and carries no shutdown notice, no migration guidance and no wind-down language. The company appears to be operating with active products.

We are recording this because that kind of stale signal propagates. If you saw the same thing and it worried you, our reading of the primary source is that the product is live.

Where it is thin

Evals. Langtrace has annotations, manual evaluation in the UI, and metrics, and that is roughly where it stops. It is not a regression-testing framework and does not try to be.

If evaluation is your primary requirement rather than tracing, DeepEval, promptfoo or Braintrust are all substantially more capable, and you would use Langtrace alongside one of them rather than instead of one.

Community and integration surface are also smaller than Langfuse’s, which is the practical cost of being the less popular option - fewer Stack Overflow answers, fewer worked examples, fewer third-party integrations.

Should you use it?

Use Langtrace if you are RAG-heavy and want real vector database visibility, you value OpenTelemetry-native portability, and AGPL on the server is acceptable to your legal team.

Don’t use it if your organisation prohibits AGPL, you need strong built-in evals, or you need a vendor with an established and published commercial model you can plan around.

Bottom line: a genuinely good tracing tool with the best vector database instrumentation in its weight class, available for nothing. The product is not the risk. The risk is a free cloud with no revenue model attached to a seed round raised around 2022, and a copyleft server license that some legal departments will reject outright. Both are manageable - self-host, and check the license early. Go in with those two things handled and it is a solid choice.

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License, funding and commercial status verified against the vendor’s own site, repository documentation and public funding databases on 31 July 2026. This is a researched directory entry - we have not yet instrumented this platform with our reference application.