DecisionLedger AI vs Credo AI
Credo AI governs the AI system with policies and assessments. DecisionLedger governs the decision the AI informs, and enforces it at runtime. See where an oversight layer ends and a governance runtime begins.
Different Problems, Different Platforms
Credo AI and DecisionLedger AI solve fundamentally different challenges. Here's how each platform approaches its core strengths.
- AI registry with use-case intake and risk classification
- Policy packs and structured impact assessments
- Fairness and risk metrics mapped to frameworks
- Compliance mapping for the EU AI Act and NIST AI RMF
- Stakeholder-friendly governance scorecards and reports
- 14 decision science methods across 298 models, so the analysis and its governance live together
- Inline AI gateway with per-call attribution and budget hard-stop before a request forwards
- Quantitative algorithmic impact assessments with statistical bias analysis and EU AI Act article scoring
- WORM decision audit on S3 Object Lock with full decision replay
- Examiner-ready evidence generated from actual governance activity, not questionnaires
- Human and AI cost on one ledger with enforceable budgets
Feature-by-Feature Comparison
| Feature | Credo AI | DecisionLedger AI |
|---|---|---|
| Category | AI governance oversight and policy management | AI governance plus decision governance in one runtime |
| Quantitative decision models | 14 decision science methods across 298 models (MCDA, Bayesian, Monte Carlo, optimization) | |
| AI use-case intake & inventory | AI registry with use-case intake and risk tiering | Agent and model registry plus decision intake with risk tiering and regulatory scope |
| Algorithmic impact assessments | Policy packs and structured questionnaires | Quantitative AIA and DPIA with statistical bias analysis and EU AI Act article scoring |
| Runtime enforcement (AI gateway) | Inline AI gateway: per-call attribution and budget hard-stop before the request forwards | |
| Bias & fairness testing | Fairness metrics via configured evidence | Built-in statistical bias auditing plus SHAP explainability |
| Evidence for auditors | Governance scorecards and assessment reports | Examiner-ready evidence generated from actual governance activity |
| Immutable audit trail | Governance record history | WORM decision audit on S3 Object Lock with full decision replay |
| Human + AI cost governance | LLM spend and labor cost on one ledger with enforceable budgets | |
| Framework coverage | EU AI Act, NIST AI RMF | EU AI Act (article-level), NIST AI RMF, ISO/IEC 42001, NYC LL144, SOX, HIPAA |
| Decision lifecycle & approvals | 7-stage decision lifecycle with approval workflows and committee voting |
Feature comparison based on publicly available documentation and product announcements.
What an AI Oversight Layer Leaves Out
Where governing the model stops and governing the decision begins.
Oversight Without the Decision
Credo AI governs the AI system as a layer of oversight, but the business decision the model informs lives in another tool. DecisionLedger governs the decision itself, linking every model run to a tracked decision and a recorded outcome.
Documentation, Not Enforcement
Policy packs and assessments document intent. They do not sit on the request path. DecisionLedger's inline AI gateway can hard-stop a non-compliant or over-budget call before it runs.
No Quantitative Decision Engine
Credo AI assesses the models you bring; it does not run decision science. DecisionLedger ships 14 methods and 298 models, so the analysis and its governance live in one place.
Evidence You Assemble vs Evidence That Accrues
Assessment reports are compiled from questionnaires. DecisionLedger generates examiner-ready evidence automatically from real governance activity, sealed in an immutable audit trail.
AI Cost Is Out of Scope
Credo AI governs risk, not spend. DecisionLedger puts LLM and human labor cost on one ledger, with budgets that warn, throttle, and block before spend runs away.
Single-Domain AI Focus
Credo AI focuses on AI and ML risk. DecisionLedger governs AI-informed decisions across HR, finance, operations, and M&A with domain-aware guardrails for HIPAA, MNPI, and the EU AI Act.
19 Patents
protecting the decision governance platform - from plugin trust verification to MCP-governed agent gateways to domain classification guardrails.