KLA vs Credo AI
Credo-style platforms are strong for inventories, assessments, and governance artifacts. KLA focuses on runtime workflow governance + evidence exports tied to real executions.
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 Credo AI tatsächlich ist
Basierend auf ihrer primären Aufgabe (und wo es Überschneidungen gibt).
Credo AI is built for program governance: inventories, assessments, policies, and standardized transparency artifacts/reports that help coordinate responsible AI work across stakeholders.
Überschneidung
- Both can support compliance teams producing artifacts and coordinating reviews.
- Both can improve audit readiness: Credo through program-level workflows, KLA through runtime decision evidence and exports.
- Many regulated teams use both: a governance system of record plus a runtime evidence layer for high-risk workflows.
Worin Credo AI exzellent ist
Erkennen Sie, was das Tool gut macht, und trennen Sie es dann von Audit-Deliverables.
- Governance program scaffolding (inventories, assessments, policies, standardized reporting).
- Helping teams coordinate compliance work across many systems and stakeholders.
Wo regulierte Teams noch eine separate Ebene benötigen
- Runtime capture of "what actually happened" in an agent workflow (actions taken, approvals, overrides, and context).
- Decision-time enforcement evidence at checkpoints (block/review/allow) for high-risk actions.
- A verifiable evidence pack export tied to executions (manifest + checksums) rather than only program artifacts.
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
- Program governance workflows: system inventories, risk assessments, policies, and reporting.
- Standardized artifacts for transparency and internal/external review.
- Coordination across stakeholders and evidence mapping at the program level.
Möglich, aber Sie bauen es
- Runtime instrumentation and collection for agent workflows (traces, actions, approvals) across teams and systems.
- Decision-time gates and approval queues for high-risk actions (with escalation and overrides).
- Evidence bundle packaging that maps runtime evidence to Annex IV/oversight deliverables, with verification artifacts.
- Retention/integrity posture for long-lived audit evidence and exports.
Konkretes reguliertes Workflow-Beispiel
Ein Szenario, das zeigt, wo jede Ebene passt.
Governance program + one high-risk workflow
A compliance team runs inventories and assessments for many AI systems. For one high-risk agent workflow (e.g., account closure recommendations), auditors also want runtime decision evidence: who approved, what policy applied, and what happened in production.
Wo Credo AI hilft
- Track inventories, owners, and risk assessments across systems.
- Produce standardized reports and transparency artifacts for stakeholders.
Wo KLA hilft
- Enforce decision-time gates on the workflow (block/review/allow) with role-aware approvals.
- Capture execution evidence (actions, approvals, sampling outcomes) tied to the exact versions running in production.
- Export a verifiable evidence pack suitable for auditor handoff (manifest + checksums).
Schnelle Entscheidung
Wann jedes wählen (und wann beide kaufen).
Wählen Sie Credo AI, wenn
- You need a governance system of record for assessments and policy workflows.
- You are standardizing risk and compliance reporting across the organization.
Wählen Sie KLA, wenn
- You need a runtime control plane around agent workflows (gates + sampling + oversight).
- You need to export audit-ready evidence bundles tied to actual executions.
Wann Sie KLA nicht kaufen sollten
- You only need program governance artifacts and do not need runtime workflow controls or evidence exports.
Wenn Sie beide kaufen
- Use Credo AI to manage inventories, policies, and assessments.
- Use KLA to generate runtime evidence and deliver verifiable exports for audits.
Was KLA nicht tut
- KLA is not designed to replace a governance system of record for inventories, assessments, and policy workflows.
- KLA is not a request gateway/proxy layer for model calls.
- 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 Credo AI 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 Credo AI (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 program artifacts to runtime execution evidence for audits (approvals, enforcement, and exports)?
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.