KLA vs LangSmith
LangSmith is excellent for tracing, evals, and annotation workflows. KLA is built for regulated workflows: decision-time policy gates, approval queues, and 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 LangSmith tatsächlich ist
Basierend auf ihrer primären Aufgabe (und wo es Überschneidungen gibt).
LangSmith is built for observing and improving LLM/agent runs: tracing, evaluation tooling, and human annotation workflows, especially when you build on LangChain/LangGraph.
Überschneidung
- Both help teams understand what happened in a run (inputs, outputs, metadata) and debug failures.
- Both can support sampling and evaluation loops, with different end goals (iteration vs audit deliverables).
- Both can export run data; the difference is whether it’s raw logs/traces or a deliverable-shaped evidence bundle.
Worin LangSmith exzellent ist
Erkennen Sie, was das Tool gut macht, und trennen Sie es dann von Audit-Deliverables.
- Developer-first tracing and debugging for agentic apps.
- Evaluation workflows, including online evaluators with filters and sampling rates.
- Annotation queues for structured human feedback on runs.
- Bulk export of trace data for pipelines and retention workflows.
- Strong fit if you are already deep in LangChain/LangGraph.
Wo regulierte Teams noch eine separate Ebene benötigen
- Decision-time approval gates for business actions (block until approved), with captured reviewer context as a workflow decision record.
- A clear separation between "human annotation" (after-the-fact review) and "human approval" (enforceable gate) for high-risk actions.
- Deliverable-shaped evidence exports mapped to Annex IV (oversight records, monitoring outcomes, manifest + checksums), not just raw traces.
- Proof layer for long retention: append-only, hash-chained integrity with verification mechanics auditors can validate.
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
- Run tracing and debugging for LLM/agent workflows.
- Evaluation tooling (including online evaluators and configurable sampling).
- Human annotation queues for labeling and review.
- Bulk data export of run/trace data.
- Team access controls (plan-dependent).
Möglich, aber Sie bauen es
- An enforceable approval gate that blocks high-risk actions in production until a reviewer approves (with escalation and overrides).
- Workflow decision records (who approved/overrode what, what they saw, and why) tied to the business action, not only to the run.
- A mapped evidence pack export (Annex IV sections to evidence), with a manifest + checksums suitable for third-party verification.
- Retention, redaction, and integrity posture (e.g., 7+ years, WORM storage, verification drills).
Konkretes reguliertes Workflow-Beispiel
Ein Szenario, das zeigt, wo jede Ebene passt.
KYC/AML adverse media escalation
An agent screens a customer, retrieves adverse media, and proposes an escalation/SAR recommendation. The high-risk action (escalation or filing) must be blocked until a designated reviewer approves.
Wo LangSmith hilft
- Debug which sources were used and why the model made a recommendation.
- Run evals to reduce false positives/false negatives and improve reviewer consistency.
- Export traces for downstream analytics and retention systems.
Wo KLA hilft
- Enforce a checkpoint that blocks escalation until the right role approves (with escalation rules).
- Capture approval/override decisions as first-class workflow records with context and rationale.
- Export a verifiable evidence bundle mapped to Annex IV and oversight requirements.
Schnelle Entscheidung
Wann jedes wählen (und wann beide kaufen).
Wählen Sie LangSmith, wenn
- You primarily need dev tracing/evals and are not being audited on workflow decisions.
- You want a tight loop inside the LangChain ecosystem.
- Your “buyer” is an engineering team optimizing prompts and reliability.
Wählen Sie KLA, wenn
- Your buyer must produce auditor-ready artifacts (Annex IV, oversight records, monitoring plans).
- You need approvals/overrides to be first-class workflow controls, not notes in a trace.
- You need one-click evidence exports with integrity verification mechanics.
Wann Sie KLA nicht kaufen sollten
- You only need observability and experimentation tooling for non-regulated apps.
- You already have a workflow engine + ticketing + retention/signing and you’re comfortable assembling evidence bundles yourself.
Wenn Sie beide kaufen
- Use LangSmith for dev iteration and evaluation loops.
- Use KLA to enforce runtime governance (checkpoints + queues) and export evidence packs for audits.
Was KLA nicht tut
- KLA is not a replacement for developer-first tracing/eval tooling used to iterate on prompts.
- KLA is not a prompt playground or prompt-versioning system.
- KLA is not a request gateway/proxy 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 LangSmith 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 LangSmith (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? - How do you prove that an approve/stop gate was enforced in production (not just annotated after the fact)?
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.