KLA vs Holistic AI
Holistic AI is positioned around EU AI Act readiness and governance workflows. KLA is the runtime control plane for agent workflows with 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 Holistic AI tatsächlich ist
Basierend auf ihrer primären Aufgabe (und wo es Überschneidungen gibt).
Holistic AI is built for EU AI Act readiness and governance work: helping teams structure classification, readiness assessments, and stakeholder reporting across AI systems.
Überschneidung
- Both support audit readiness: Holistic through program structure and reporting, KLA through runtime decision evidence and exports.
- Both can be used together: governance dashboards for breadth, and workflow decision governance for depth in high-risk paths.
- Both align to “deliverables” thinking; the difference is whether deliverables are assembled from process declarations or generated from execution evidence.
Worin Holistic AI exzellent ist
Erkennen Sie, was das Tool gut macht, und trennen Sie es dann von Audit-Deliverables.
- Structuring EU AI Act readiness work (registration, classification, reporting).
- Helping stakeholders coordinate governance and assurance programs.
Wo regulierte Teams noch eine separate Ebene benötigen
- Decision-time workflow controls: policy checkpoints + role-aware queues for approvals and overrides.
- Evidence generation from actual executions (actions, approvals, sampling outcomes), not only declared processes.
- Verifiable export bundles (manifest + checksums) that map evidence to Annex IV deliverables for auditor handoff.
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
- Readiness and governance workflows (classification, registration, reporting).
- Dashboards and artifacts for communicating compliance posture to stakeholders.
- Program coordination across teams and systems.
Möglich, aber Sie bauen es
- Runtime capture of workflow execution evidence (actions, approvals, overrides) tied to production versions.
- Policy checkpoints that can block/review/allow high-risk actions in production.
- A packaged evidence export mapped to Annex IV/oversight deliverables with verification artifacts.
- Retention and integrity posture for long-lived audit evidence.
Konkretes reguliertes Workflow-Beispiel
Ein Szenario, das zeigt, wo jede Ebene passt.
EU AI Act readiness + a governed pilot workflow
A team completes readiness assessments and reporting across multiple AI systems. For a single high-risk agent workflow (e.g., claims payout recommendations), auditors still ask for runtime evidence: who approved, what policy applied, and how integrity is verified.
Wo Holistic AI hilft
- Coordinate readiness work, owners, and reporting across the organization.
- Generate dashboards and artifacts for program management.
Wo KLA hilft
- Enforce decision-time controls in the pilot workflow (checkpoints + approvals + overrides).
- Capture evidence from actual executions (including sampling outcomes) with policy/version context.
- Export a verifiable evidence pack for auditors and internal reviewers.
Schnelle Entscheidung
Wann jedes wählen (und wann beide kaufen).
Wählen Sie Holistic AI, wenn
- You need readiness reporting, dashboards, and program coordination across many systems.
Wählen Sie KLA, wenn
- You need to govern agent workflows at runtime and produce evidence packs automatically.
- You need Annex IV-style documentation backed by execution evidence and integrity proofs.
Wann Sie KLA nicht kaufen sollten
- You only need governance planning artifacts and are not yet shipping governed workflows.
Wenn Sie beide kaufen
- Use Holistic AI to structure program work and ownership.
- Use KLA to generate runtime evidence and deliver exportable audit packs.
Was KLA nicht tut
- KLA is not designed to replace governance program tooling for inventories, readiness assessments, and enterprise reporting.
- 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 Holistic 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 Holistic 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 demonstrate runtime enforcement and workflow decision evidence (not just program documentation) during an audit?
Quellen
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Hinweis: Produktfähigkeiten ändern sich. Wenn Sie etwas Veraltetes entdecken, melden Sie es bitte über /contact.