KLA vs Fiddler
Fiddler is strong for AI observability, monitoring, and guardrails programs. KLA focuses on workflow decision governance (checkpoints + queues) and verifiable 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 Fiddler tatsächlich ist
Basierend auf ihrer primären Aufgabe (und wo es Überschneidungen gibt).
Fiddler is built for AI observability and monitoring: tracking performance, risk signals, and guardrail outcomes across AI systems. It is a strong fit when your program starts with measurement and reporting.
Überschneidung
- Both can support risk/quality measurement programs and ongoing monitoring signals.
- Both can support "prove it" conversations. The difference is whether proof is packaged from workflow decisions or assembled from monitoring outputs.
- Both can be used together: monitoring for broad coverage, and a control plane for enforcing approval gates in specific workflows.
Worin Fiddler exzellent ist
Erkennen Sie, was das Tool gut macht, und trennen Sie es dann von Audit-Deliverables.
- Unified AI observability positioning (monitoring, evaluation, safety/guardrails framing).
- Strong fit when the program starts with model/agent monitoring, reporting, and guardrail signals.
Wo regulierte Teams noch eine separate Ebene benötigen
- Decision-time workflow governance: who can approve/override/stop an agent action, and how that gate is enforced.
- Policy checkpoints embedded in the workflow that can block/review/allow actions (with evidence of enforcement).
- Deliverable-shaped evidence exports (Annex IV mapping + oversight records + manifest + checksums), not only monitoring dashboards.
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
- Monitoring and reporting across AI systems (quality, safety, and risk signals).
- Guardrail and evaluation framing for responsible AI programs.
- Dashboards/alerts for continuous monitoring and incident response workflows.
Möglich, aber Sie bauen es
- A decision-time gate that blocks high-risk workflow actions until approved (with escalation and override rules).
- Workflow decision records (approvals/overrides) tied to business actions, not just model outputs.
- A packaged evidence bundle export mapped to Annex IV/oversight deliverables, with verification artifacts.
- Retention and integrity controls for long-lived audit records.
Konkretes reguliertes Workflow-Beispiel
Ein Szenario, das zeigt, wo jede Ebene passt.
Credit underwriting recommendation
An agent proposes approve/deny decisions with supporting rationale. Monitoring tells you how the system behaves over time; regulated workflows often also require a decision-time gate before the final decision is issued.
Wo Fiddler hilft
- Monitor drift, performance regressions, and guardrail outcomes across models and cohorts.
- Trigger investigations when risk signals breach thresholds.
Wo KLA hilft
- Enforce an approval checkpoint before a high-impact decision is issued or acted on.
- Capture who approved/overrode the recommendation (and what they saw) as an auditable decision record.
- Export a verifiable evidence pack for reviewers and auditors (manifest + checksums).
Schnelle Entscheidung
Wann jedes wählen (und wann beide kaufen).
Wählen Sie Fiddler, wenn
- Your primary requirement is broad AI monitoring and reporting across many models.
- You are building a measurement program first and governance controls later.
Wählen Sie KLA, wenn
- You need to govern workflow actions (not only monitor models) with approvals and policy gates.
- You need evidence packs with integrity verification for audits.
Wann Sie KLA nicht kaufen sollten
- You only need monitoring dashboards and alerts and don’t require approval queues or evidence exports.
Wenn Sie beide kaufen
- Use Fiddler to understand performance and risk signals.
- Use KLA to enforce controls at decision time and export the evidence pack auditors ask for.
Was KLA nicht tut
- KLA is not designed to replace broad AI monitoring platforms for organization-wide reporting.
- KLA is not a request gateway/proxy for model access.
- KLA is not a prompt experimentation suite.
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 Fiddler 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 Fiddler (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 connect monitoring signals to enforceable workflow gates and a packaged evidence export for audits?
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.