Traceloop

Traceloop is an OpenTelemetry-based LLM observability and evaluation platform built around...

7.8/10Useful

Active

Free Forever $0/month up to 50K spans / Enterprise custom

Best plan

Use Free Forever for a low-risk proof of tracing, prompt...

Risk: The ServiceNow transition changes procurement and roadmap...

Try Traceloop free

Editorial · no paid placements

Should you use it?

Traceloop is an OpenTelemetry-based LLM observability and evaluation platform built around OpenLLMetry. Pick it when traces, quality checks, prompt management, and production monitoring need to fit an OpenTelemetry stack. Verify ServiceNow transition details before buying for enterprise use.

Buy ifTeams already using OpenTelemetry for production observability
PickUse Free Forever for a low-risk proof of tracing, prompt management, monitoring, and eval dashboards under 50K spans/month. Use Enterprise when production AI observability needs more than 50K spans, unlimited seats, custom retention, on-prem or restricted deployment, and ServiceNow AI Control Tower alignment
Skip ifTeams that only need a Python metric framework

Plan guidance

What to buy

Best planUse Free Forever for a low-risk proof of tracing, prompt management, monitoring, and eval dashboards under 50K spans/month. Use Enterprise when production AI observability needs more than 50K spans, unlimited seats, custom retention, on-prem or restricted deployment, and ServiceNow AI Control Tower alignment

Watch: The ServiceNow transition changes procurement and roadmap...

Price rangeFree Forever $0/month up to 50K spans / Enterprise custom

$0/month

Upgrade only ifNot for teams that only need a python metric framework

The ServiceNow transition changes procurement and roadmap...

Current pricing source: Traceloop pricing

Fit

Use it for this, skip it for that

Best for

Teams already using OpenTelemetry for production observability
LLM apps that need traces, quality checks, prompt management, and dashboards
Enterprises evaluating ServiceNow AI Control Tower alignment
Teams that want an open-source instrumentation layer through OpenLLMetry

Avoid if

Teams that only need a Python metric framework
Buyers who want a stable standalone vendor without acquisition transition questions
Teams that need model routing before observability
Low-volume prototypes that do not need trace retention or quality dashboards

Watch out: The ServiceNow transition changes procurement and roadmap risk; buyers should verify product continuity, support, data handling, and whether they are buying standalone Traceloop or ServiceNow AI Control Tower.

Recent changes

Only what affects the decision

Jun 28, 2026
Free Forever
Listed for up to 50K spans/month, up to 5 seats, 24 hours of data retention, monitoring dashboard, evaluation dashboard, and prompt management
Traceloop pricing
Jun 28, 2026
Enterprise
Listed for greater than 50K spans/month, unlimited seats, custom retention, and production deployment needs
Traceloop pricing
Jun 28, 2026
OpenLLMetry
The OpenLLMetry repository is Apache-2.0 licensed
OpenLLMetry license

Alternatives

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Build comparison

Proof and score mathVerified Jun 28

Proof

Why this recommendation is trusted

EvidenceTraceloop docs

Source: Registered source
Freshness: Review due
Confidence: Low confidence
Verified: Jun 28, 2026
Review: Jul 12, 2026
Volatility: Volatile

Stale source traceloop-pricing.

Editorial score

Unweighted average of 4 axes · confidence high

Utility8/10
How much real work it can do for a competent operator, end to end.
Value8/10
What you get for the dollar relative to the closest alternative.
Moat7/10
How hard it would be for a competitor to replicate the underlying advantage.
Longevity8/10
How likely the product is to still be best-in-class 24 months out.

Verified facts

Best ForTeams that want OpenTelemetry-based observability and evaluation for LLM applications, with traces, quality checks, prompt management, monitoring, and debugging workflows.
highDrifts2026-06-28Traceloop docs
Pricing AnchorTraceloop pricing lists Free Forever at $0/month up to 50K spans/month and Enterprise as a custom plan for greater than 50K spans/month, unlimited seats, and custom data retention.
highVolatile2026-06-28Traceloop pricing
Watch Out ForThe ServiceNow transition changes procurement and roadmap risk; buyers should verify product continuity, support, data handling, and whether they are buying standalone Traceloop or ServiceNow AI Control Tower.
highVolatile2026-06-28Traceloop joins ServiceNow
Open Source Or LocalOpenLLMetry is Apache-2.0 licensed and described as open-source observability for LLM applications built on OpenTelemetry.
highDrifts2026-06-28OpenLLMetry repository
Acquisition StatusTraceloop announced in March 2026 that it is joining ServiceNow and that its technology will become part of ServiceNow's AI Control Tower.
highVolatile2026-06-28Traceloop joins ServiceNow

Full review notesLong-form details, FAQ, and source history

Traceloop is an LLM requests, monitor quality, test changes to prompts or models, manage prompts, and debug production behavior.

The June 2026 context matters: Traceloop announced that it is joining ServiceNow, and the pricing page carries the same banner. Buyers should evaluate both the standalone Traceloop path and ServiceNow AI Control Tower alignment.

System Verdict

Pick Traceloop when OpenTelemetry is the observability standard. It is strongest for teams that want LLM traces, quality checks, prompt management, monitoring, and OpenTelemetry-compatible instrumentation.

Skip it when the whole job is eval design. Ragas or DeepEval fit better when a developer only needs code-first metrics and CI tests.

Best plan guidance: use Free Forever under 50K spans/month for proof of value. Use Enterprise when span volume, retention, deployment, ServiceNow integration, and support become the real purchase.

Key Facts


Core job	LLM observability, traces, evaluations, monitoring, prompt management
Open-source layer	OpenLLMetry
License	Apache-2.0 for OpenLLMetry
Free Forever	$0/month, up to 50K spans/month
Free limits	Up to 5 seats, 24 hours retention
Enterprise	Custom, greater than 50K spans/month, unlimited seats, custom retention
Company status	Joining ServiceNow, with AI Control Tower alignment

When To Pick Traceloop

You already use OpenTelemetry. OpenLLMetry builds on standard observability concepts and can send data to existing backends.
You need production traces. Traceloop is designed for tracing every request and debugging LLM application behavior.
You need quality checks in monitoring. The platform positions built-in quality checks, dashboards, alerts, and evaluation workflows around live traffic.
You want prompt and model experiments. Docs and product copy emphasize prompt management and testing model or prompt changes.
You are a ServiceNow enterprise. The acquisition path may make Traceloop more attractive if AI Control Tower is already on the roadmap.

When To Pick Something Else

Hosted eval operations: Braintrust when datasets, experiments, review, scoring, and release evidence are first.
Open-source AI observability: Arize Phoenix when traces, prompt iteration, evals, datasets, and experiments should sit in an engineering-native open-source platform.
Code-first RAG evals: Ragas when RAG metrics and test data are the key job.
Open-source LLM test framework: DeepEval when Python eval tests and metrics are the primary workflow.
Gateway control: Portkey or Helicone when live routing, caching, fallback, budgets, and provider policy are the main pain.

Pricing

Traceloop pricing was checked on June 28, 2026 against the official pricing page.

Plan	Public price	Included shape	Buyer fit
Free Forever	$0/month	Up to 50K spans/month, up to 5 seats, 24 hours retention, monitoring dashboard, evaluation dashboard, prompt management	Evaluation and early production tests
Enterprise	Custom	More than 50K spans/month, unlimited seats, custom retention, production deployment	Teams operating serious LLM apps
OpenLLMetry	Free open source	Apache-2.0 instrumentation layer	Teams that want open instrumentation or backend portability

The practical buying advice: span volume and retention decide the bill. Agents, tool calls, retries, and RAG pipelines can multiply spans quickly.

Failure Modes

Acquisition transition risk is real. Verify product roadmap, support channel, contract path, and whether future purchase goes through ServiceNow.
Spans can grow faster than requests. Multi-step agents and RAG systems may emit many spans per user action.
Observability is not eval design. Teams still need representative datasets, rubrics, and acceptance thresholds.
Self-hosting requires operations work. On-prem or restricted environments need infrastructure, upgrades, storage, and security ownership.
OpenTelemetry does not solve data policy. Traces can contain prompts, retrieved context, customer data, and tool outputs, so retention and redaction rules matter.

Methodology

This page was produced by the aipedia.wiki editorial pipeline. Scoring follows the four-dimension rubric at /about/scoring/ (Utility x Value x Moat x Longevity, unweighted average). Last verified 2026-06-28 against Traceloop docs, pricing, OpenLLMetry repository, license, and ServiceNow acquisition update.

FAQ

Is Traceloop free? Traceloop lists a Free Forever plan at $0/month for up to 50K spans/month. Enterprise is custom.

Is OpenLLMetry open source? Yes. The OpenLLMetry repository is Apache-2.0 licensed.

Traceloop vs Arize Phoenix? Traceloop is the OpenTelemetry/OpenLLMetry lane with ServiceNow transition context. Arize Phoenix is an open-source AI observability platform for traces, evals, prompts, datasets, and experiments, with Arize AX as the hosted path.

Sources

Traceloop docs: LLM observability, testing, monitoring, and OpenTelemetry setup
Traceloop pricing: Free Forever and Enterprise plan details
OpenLLMetry repository: OpenTelemetry-based LLM observability project
OpenLLMetry license: Apache-2.0 license
Traceloop joins ServiceNow: ServiceNow transition and AI Control Tower context

Category: AI Infrastructure · AI Automation · AI Coding
Alternatives: Arize Phoenix · LangWatch · Braintrust · LangSmith

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News writers

According to aipedia.wiki Editorial at aipedia.wiki (https://aipedia.wiki/tools/traceloop/)

APA

aipedia.wiki Editorial. (2026). Traceloop: Editorial Review. aipedia.wiki. Retrieved August 3, 2026, from https://aipedia.wiki/tools/traceloop/

MLA 9

aipedia.wiki Editorial. "Traceloop: Editorial Review." aipedia.wiki, 2026, https://aipedia.wiki/tools/traceloop/. Accessed August 3, 2026.

Chicago

aipedia.wiki Editorial. 2026. "Traceloop: Editorial Review." aipedia.wiki. https://aipedia.wiki/tools/traceloop/.

BibTeX

@misc{traceloop-editorial-review-2026,
  author = {{aipedia.wiki Editorial}},
  title = {Traceloop: Editorial Review},
  year = {2026},
  publisher = {aipedia.wiki},
  url = {https://aipedia.wiki/tools/traceloop/},
  note = {Accessed: 2026-08-02}
}

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