Watch: The ServiceNow transition changes procurement and roadmap...
Traceloop
Traceloop is an OpenTelemetry-based LLM observability and evaluation platform built around...
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...
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 if Teams already using OpenTelemetry for production observability
- Pick Use 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 if Teams that only need a Python metric framework
Plan guidance
What to buy
$0/month
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
- 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 - Enterprise
Listed for greater than 50K spans/month, unlimited seats, custom retention, and production deployment needs
Traceloop pricing - OpenLLMetry
The OpenLLMetry repository is Apache-2.0 licensed
OpenLLMetry license
Alternatives
Best swaps
Open AI collaboration hub for models, datasets, Spaces, inference endpoints, evaluations, and enterprise ML workflows.
Free hub access; Pro $9/mo; Team $20/user/mo; Enterprise from $50/user/mo; paid compute/storage · 9.3/10 LiteLLMOpen-source LLM gateway and Python SDK for one OpenAI-compatible interface across 100+ model providers, with routing, virtual ke
Free MIT core outside enterprise directory; Enterprise custom · 8.8/10 promptfooOpen-source LLM evaluation, red teaming, vulnerability scanning, guardrails, model security, MCP proxy, code scanning, and enter
Community free / Enterprise custom / On-Premise custom · 8.8/10Proof and score math Verified Jun 28
Proof
Why this recommendation is trusted
- Source
- Registered source
- Freshness
- Current
- Confidence
- High confidence
- Verified
- Review
- Volatility
- Volatile
High-volatility evidence needs frequent review.
Editorial score
Unweighted average of 4 axes · confidence high
- Utility 8/10
How much real work it can do for a competent operator, end to end.
- Value 8/10
What you get for the dollar relative to the closest alternative.
- Moat 7/10
How hard it would be for a competitor to replicate the underlying advantage.
- Longevity 8/10
How likely the product is to still be best-in-class 24 months out.
Verified facts
- Best For Teams that want OpenTelemetry-based observability and evaluation for LLM applications, with traces, quality checks, prompt management, monitoring, and debugging workflows.
- Pricing Anchor Traceloop 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.
- Watch Out For 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.
- Open Source Or Local OpenLLMetry is Apache-2.0 licensed and described as open-source observability for LLM applications built on OpenTelemetry.
- Acquisition Status Traceloop announced in March 2026 that it is joining ServiceNow and that its technology will become part of ServiceNow's AI Control Tower.
Full review notes Long-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
Related
- Category: AI Infrastructure · AI Automation · AI Coding
- Alternatives: Arize Phoenix · LangWatch · Braintrust · LangSmith
Reader reviews
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Cite this page For journalists, researchers, and bloggers
According to aipedia.wiki Editorial at aipedia.wiki (https://aipedia.wiki/tools/traceloop/) aipedia.wiki Editorial. (2026). Traceloop: Editorial Review. aipedia.wiki. Retrieved July 2, 2026, from https://aipedia.wiki/tools/traceloop/ aipedia.wiki Editorial. "Traceloop: Editorial Review." aipedia.wiki, 2026, https://aipedia.wiki/tools/traceloop/. Accessed July 2, 2026. aipedia.wiki Editorial. 2026. "Traceloop: Editorial Review." aipedia.wiki. https://aipedia.wiki/tools/traceloop/. @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: 2026-07-02}
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