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Comparison

KLA vs Traceloop (OpenLLMetry)

Traceloop/OpenLLMetry is excellent for OpenTelemetry-first tracing. KLA adds governance controls and verifiable evidence exports for audits.

Tracing is necessary. Regulated audits usually ask for decision governance + proof: enforceable policy gates and approvals, packaged as a verifiable evidence bundle (not just raw logs).

For platform teams who want OpenTelemetry-first instrumentation for LLM apps and agent workflows.

Last updated: Dec 17, 2025 · Version v1.0 · Not legal advice.

Audience

Who this page is for

A buyer-side framing (not a dunk).

For platform teams who want OpenTelemetry-first instrumentation for LLM apps and agent workflows.

Tip: if your buyer must produce Annex IV / oversight records / monitoring plans, start from evidence exports, not from tracing.
Context

What Traceloop / OpenLLMetry is actually for

Grounded in their primary job (and where it overlaps).

Traceloop/OpenLLMetry is built for OpenTelemetry-based instrumentation of LLM apps: capture traces and export them into your existing observability stack with minimal vendor lock-in.

Overlap

  • Both can be OpenTelemetry-friendly and fit into existing telemetry pipelines.
  • Both support “what happened?” debugging and traceability — KLA extends this into decision governance and evidence exports.
  • A common pattern is: instrument with OpenTelemetry for observability, then add decision governance only where audited.
Strengths

What Traceloop / OpenLLMetry is excellent at

Recognize what the tool does well, then separate it from audit deliverables.

  • OpenTelemetry-based instrumentation and tracing for LLM apps.
  • Non-intrusive approach: export traces into your existing observability stack.

Where regulated teams still need a separate layer

  • Workflow approvals/overrides and role-aware decision authority captured as decision records tied to business actions.
  • Decision-time policy checkpoints that gate actions with enforceable controls (block/review/allow).
  • Evidence Room style export bundles (manifest + checksums) mapped to Annex IV/oversight deliverables, not just traces.
Nuance

Out-of-the-box vs build-it-yourself

A fair split between what ships as the primary workflow and what you assemble across systems.

Out of the box

  • OpenTelemetry-based tracing/instrumentation for LLM apps.
  • Exporting telemetry into existing observability destinations.

Possible, but you build it

  • A decision-time approval gate for high-risk actions (with escalation and overrides).
  • Decision records with reviewer context and rationale tied to the action, not only the trace.
  • A packaged evidence export mapped to Annex IV/oversight deliverables with verification artifacts.
  • Retention and integrity posture suitable for audits (multi-year, verification drills, redaction rules).
Example

Concrete regulated workflow example

One scenario that shows where each layer fits.

KYC tool-call governance

An agent can call internal tools to fetch customer data and propose a compliance action. OpenTelemetry traces help debug behavior; regulated workflows often also require a decision-time approval gate before the action is executed.

Where Traceloop / OpenLLMetry helps

  • Instrument runs and export traces to your observability tooling for debugging and incident response.
  • Standardize telemetry across multiple apps and providers.

Where KLA helps

  • Block the high-risk action until an authorized reviewer approves.
  • Capture approval/override records as auditable decision evidence with context.
  • Export a verifiable evidence bundle for auditors and internal governance review.
Decision

Quick decision

When to choose each (and when to buy both).

Choose Traceloop / OpenLLMetry when

  • You want OpenTelemetry-first tracing integrated into existing observability tooling.

Choose KLA when

  • You need governance controls and audit-ready evidence exports for regulated workflows.

When not to buy KLA

  • You only need instrumentation and tracing and do not need governance controls or evidence exports.

If you buy both

  • Use OpenTelemetry/Traceloop for deep observability and exporting telemetry to your stack.
  • Use KLA for governance controls and audit-ready evidence bundles.

What KLA does not do

  • KLA is not a tracing SDK or OpenTelemetry replacement.
  • KLA is not a request gateway/proxy layer for model calls.
  • KLA is not a prompt experimentation suite.
KLA

KLA’s control loop (Govern / Measure / Prove)

What “audit-grade evidence” means in product primitives.

Govern

  • Policy-as-code checkpoints that block or require review for high-risk actions.
  • Role-aware approval queues, escalation, and overrides captured as decision records.

Measure

  • Risk-tiered sampling reviews (baseline + burst during incidents or after changes).
  • Near-miss tracking (blocked / nearly blocked steps) as a measurable control signal.

Prove

  • Tamper-proof, append-only audit trail with external timestamping and integrity verification.
  • Evidence Room export bundles (manifest + checksums) so auditors can verify independently.

Note: some controls (SSO, review workflows, retention windows) are plan-dependent — see /pricing.

Download

RFP checklist (downloadable)

A shareable procurement artifact (backlink magnet).

RFP CHECKLIST (EXCERPT)
# RFP checklist: KLA vs Traceloop (OpenLLMetry)

Use this to evaluate whether “observability / gateway / governance” tooling actually covers audit deliverables for regulated agent workflows.

## Must-have (audit deliverables)
- Annex IV-style export mapping (technical documentation fields → evidence)
- Human oversight records (approval queues, escalation, overrides)
- Post-market monitoring plan + risk-tiered sampling policy
- Tamper-evident audit story (integrity checks + long retention)

## Ask Traceloop / OpenLLMetry (and your team)
- Can you enforce decision-time controls (block/review/allow) for high-risk actions in production?
- How do you distinguish “human annotation” from “human approval” for business actions?
- Can you export a self-contained evidence bundle (manifest + checksums), not just raw logs/traces?
- What is the retention posture (e.g., 7+ years) and how can an auditor verify integrity independently?
- If you already have OpenTelemetry traces, how do you produce a verifiable evidence pack with approvals and policy enforcement records?
Links

Related resources

Evidence pack checklist

/resources/evidence-pack-checklist

Open

Annex IV template pack

/annex-iv-template

Open

EU AI Act compliance hub

/eu-ai-act

Open

Compare hub

/compare

Open

Request a demo

/book-demo

Open
References

Sources

Public references used to keep this page accurate and fair.

Note: product capabilities change. If you spot something outdated, please report it via /contact.