How can Traceloop assist with AI monitoring and observability?

Traceloop assists with AI monitoring and observability by tracking model performance, errors, and execution metrics in real-time.

How can Traceloop help with AI observability?

Traceloop helps with AI observability by monitoring model performance, logging outputs, and providing insights for debugging.

How can Traceloop help monitor AI model performance?

Traceloop helps monitor AI model performance by providing logging, metrics tracking, and anomaly detection.

How can Traceloop support AI model monitoring?

Traceloop supports AI model monitoring by tracking performance, metrics, and operational health.

How does Traceloop support monitoring and observability of AI models?

Traceloop supports monitoring and observability of AI models by tracking performance, logging events, and providing detailed analytics.

Reviewed · Updated 2026-06-19

Traceloop

AI observability and workflow platform for monitoring experiments and tracking model performance.

Reviewed by the Conversion Gems editorial team · 2026-06-19

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Pricing

Paid

Best for

Developers

Category

AI Development

The bottom line

The go-to open-standards LLM observability layer for AI teams that want vendor-neutral traces and automated quality gates.

7.6

Our score

7.6 / 10

Conversion Gems editorial verdict

Free up to 50K spans/mo; Enterprise custom

Features8/10

8 - strong LLM-specific tracing, built-in evals, drift detection, CI/CD quality gates, and custom evaluators across 20+ providers and major frameworks.

Value7/10

7 - generous free tier for exploration, but the jump from free to opaque Enterprise pricing with no self-serve mid-tier is a gap for growing teams.

Ease of use8/10

8 - one-line SDK setup and OpenTelemetry familiarity accelerate onboarding; advanced custom evaluators add some complexity.

Ecosystem8/10

8 - 20+ LLM providers, LangChain/LlamaIndex/CrewAI frameworks, 25+ observability platform integrations, and AWS/GCP/Azure Marketplace listings.

Support6/10

6 - dedicated Slack and on-prem support locked to Enterprise; free tier support is limited, and the ServiceNow acquisition clouds long-term commitments.

What it really is

Traceloop — LLM observability and reliability platform built on OpenTelemetry.

Our take

Traceloop is an LLM-specific observability tool that traces prompts, responses, latency, and quality through its open-source OpenLLMetry SDK. The DB has both the pricing and price tier wrong — there is no $29/month plan; Traceloop offers a Free Forever tier (up to 50K spans/month) plus custom Enterprise pricing, making it freemium not paid. Acquired by ServiceNow in March 2026, the product remains focused on helping AI teams ship reliable LLM applications with automated CI/CD quality gates and real-time drift detection.

Why we rate it

OpenTelemetry-native architecture and multi-language support (Python, TypeScript, Go, Ruby) make Traceloop the least lock-in-heavy LLM observability option on the market. The OpenLLMetry OSS library plugs into 25+ existing observability platforms, so teams with Datadog or Grafana already in-house can adopt it without a new SaaS dashboard.

The catch

The free tier's 24-hour data retention makes it impractical for real production debugging — you'll hit Enterprise (opaque, contact-sales pricing) with no self-serve paid middle tier. ServiceNow's 2026 acquisition also introduces roadmap uncertainty for independent users.

Best for

LLM app teams wanting open-standards tracing via OpenTelemetry without vendor lock-in

MLOps teams enforcing automated quality gates and drift detection in CI/CD pipelines

Enterprises requiring SOC 2 and HIPAA-compliant AI application observability

Not good for

Teams monitoring traditional ML models (non-LLM) — focus is entirely on language models

Solo developers on the free tier who need more than 24 hours of trace history

Organizations wanting a fully self-hosted open-source stack — dashboards require the managed cloud service

Friction report

Time to value

Fast: one line of code instruments an LLM app and surfaces traces in the dashboard immediately.

Scale breakpoint

At >50K spans/month the free tier ends with no self-serve paid option — teams must contact sales for custom Enterprise pricing.

Walled garden

Low: OpenTelemetry-based instrumentation and open-source SDK mean instrumentation is portable; switching away does not require rewriting tracing code.

Frequently Asked Questions

Alternatives

Step up

Datadog LLM Observability for enterprise-grade unified monitoring across the full technology stack.

Lighter alternative

OpenLLMetry (self-hosted, Apache 2.0) for teams that want pure OSS tracing wired into an existing observability backend.

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