KLA vs Langfuse
Langfuse is a strong open-source LLM engineering platform for traces, evals, and prompt management. KLA adds decision-time workflow governance + auditor-ready evidence exports.
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 ML platform, compliance, risk, and product teams shipping agentic workflows into regulated environments.
Zuletzt aktualisiert: 17. Dez. 2025 · Version v1.0 · Keine Rechtsberatung.
Für wen diese Seite ist
Eine Einordnung aus Käufersicht (neutral gehalten).
For ML platform, compliance, risk, and product teams shipping agentic workflows into regulated environments.
Wofür Langfuse tatsächlich ist
Basierend auf ihrer primären Aufgabe (und wo es Überschneidungen gibt).
Langfuse is built for LLM engineering: tracing, prompt management, and evaluation workflows. It is open source and self-hostable; some enterprise admin features (SSO/RBAC/audit logs) depend on edition.
Überschneidung
- Both provide run histories and telemetry you can use for debugging and analysis.
- Both support human review workflows: Langfuse for evaluation/annotation, KLA for decision-time approvals in regulated actions.
- Both can coexist: Langfuse for prompt iteration and eval loops, KLA for enforceable workflow controls and evidence bundles.
Worin Langfuse exzellent ist
Erkennen Sie, was das Tool gut macht, und trennen Sie es dann von Audit-Deliverables.
- Open-source, self-hostable tracing for LLM/agent workflows.
- Prompt management and collaboration for versioned iteration.
- Evaluation workflows and human annotation for labeling/review.
- Enterprise-grade administration features (e.g., SSO/RBAC/audit logs), depending on edition.
Wo regulierte Teams noch eine separate Ebene benötigen
- Decision-time workflow gates that block business actions until the right role approves (with escalation and override procedures).
- A clear separation between platform audit logs (who changed settings) and workflow decision records (who approved an agent action).
- Evidence packs mapped to Annex IV deliverables (oversight records, monitoring outcomes, manifest + checksums) rather than raw trace exports.
- Integrity + retention posture suitable for long-lived compliance records (verification drills, redaction rules, retention policies).
Out-of-the-box vs. selbst bauen
Eine faire Aufteilung zwischen dem, was als primärer Workflow ausgeliefert wird, und dem, was Sie über Systeme hinweg zusammenbauen.
Sofort einsatzbereit
- Tracing and metrics for LLM/agent runs (self-hostable).
- Prompt management/versioning workflows.
- Evaluation tooling and human annotation for labeling and review.
- Exports of run data and (where applicable) platform audit logs.
- Enterprise controls like SSO/RBAC (edition-dependent).
Möglich, aber Sie bauen es
- A policy checkpoint that can block a high-risk workflow action until a reviewer approves (not just annotate after execution).
- Role-aware approval queues and escalation tied to business actions (send email, submit a report, approve a payout).
- A deliverable-shaped evidence export (Annex IV mapping + manifest + checksums) for auditor handoff.
- Retention, integrity, and redaction posture aligned to your compliance program (often 7+ years).
Konkretes reguliertes Workflow-Beispiel
Ein Szenario, das zeigt, wo jede Ebene passt.
Claims triage + payout recommendation
An agent summarizes claim evidence and proposes a payout or denial recommendation. The high-risk action is paying out or denying coverage, which should be blocked until an adjuster approves.
Wo Langfuse hilft
- Trace and debug the run to understand inputs, outputs, and failure modes.
- Evaluate recommendations over time and label outcomes for quality improvements.
- Manage prompt changes and compare performance across versions.
Wo KLA hilft
- Enforce a checkpoint that blocks payout/denial until an authorized approver signs off.
- Capture approvals, escalations, and overrides with reviewer context as audit evidence.
- Export an Evidence Room-style bundle mapped to oversight + Annex IV documentation.
Schnelle Entscheidung
Wann jedes wählen (und wann beide kaufen).
Wählen Sie Langfuse, wenn
- Your primary goal is prompt management + eval loops for improving LLM output quality.
- You want a self-hosted observability stack for engineering teams.
Wählen Sie KLA, wenn
- You need workflow governance: who can approve, override, or stop an agent action, with evidence.
- You need to generate Annex IV-ready exports and evidence bundles for audits.
- You want sampling and near-miss tracking positioned as controls, not only metrics.
Wann Sie KLA nicht kaufen sollten
- You only need traces, prompt management, and annotation for non-regulated workflows.
- You already have approval gates and evidence assembly handled across existing systems.
Wenn Sie beide kaufen
- Use Langfuse for experimentation, prompt versioning, and evaluation labeling.
- Use KLA to govern production workflows and export audit-ready evidence bundles.
Was KLA nicht tut
- KLA is not a full prompt management and experimentation suite.
- KLA is not trying to replace open-source observability stacks used for debugging and iteration.
- KLA is not a request gateway/proxy layer for model calls.
KLAs Kontrollschleife (Govern / Measure / Prove)
Was „auditfähige Nachweise“ in Produktprimitiven bedeutet.
Steuern
- Policy-as-Code-Checkpoints, die hochriskante Aktionen blockieren oder eine Prüfung erfordern.
- Rollenbasierte Genehmigungswarteschlangen, Eskalation und Übersteuerungen, erfasst als Entscheidungsaufzeichnungen.
Messen
- Risikogestaffelte Sampling-Reviews (Baseline + Burst während Vorfällen oder nach Änderungen).
- Near-miss-Tracking (blockierte / fast blockierte Schritte) als messbares Kontrollsignal.
Nachweisen
- Manipulationssicherer, Append-only-Audit-Trail mit externer Zeitstempelung und Integritätsverifizierung.
- Evidence Room Export-Bundles (Manifest + Prüfsummen), damit Prüfer unabhängig verifizieren können.
Hinweis: Einige Kontrollen (SSO, Review-Workflows, Aufbewahrungsfristen) sind planabhängig. Siehe /pricing.
RFP-Checkliste (herunterladbar)
Ein teilbares Beschaffungsdokument.
# RFP-Checkliste: KLA vs Langfuse Verwenden Sie dies, um zu bewerten, ob „Observability / Gateway / Governance“-Tooling tatsächlich Audit-Deliverables für regulierte Agenten-Workflows abdeckt. ## Pflicht (Audit-Deliverables) - Annex IV-Export-Mapping (technische Dokumentationsfelder -> Nachweise) - Human-Oversight-Aufzeichnungen (Genehmigungswarteschlangen, Eskalation, Übersteuerungen) - Post-Market-Monitoring-Plan + risikogestaffelte Sampling-Policy - Manipulationssichere Audit-Story (Integritätschecks + lange Aufbewahrung) ## Fragen Sie Langfuse (und Ihr 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 rely on platform audit logs, how do you produce workflow decision records (approvals/overrides) for regulated business actions?
Quellen
Öffentliche Referenzen, die verwendet wurden, um diese Seite genau und fair zu halten.
Hinweis: Produktfähigkeiten ändern sich. Wenn Sie etwas Veraltetes entdecken, melden Sie es bitte über /contact.