AI governance that goes model deep

The Credo AI alternative that turns
policies into proof

Credo AI governs policies. Deeploy governs models, with controls, real-time monitoring, and technical evidence that proves compliance.

The problem with
policy-only governance

Your compliance team uses Credo AI to catalog AI use cases and align policies. That’s a great start.

But when regulators ask — “How do you prove this model isn’t biased? Show us the technical evidence.” — can you provide proof?

One platform. Two layers. Complete governance.

Credo AI stops at the policy layer. Deeploy delivers both.

Policy & framework layer

(What Deeploy & Credo AI do)

Technical evidence layer

(What only Deeploy does)

How Deeploy compares to Credo AI

Credo AI helps you track compliance on paper. Deeploy turns it into real, operational controls.

Feature
Deeploy
Credo AI
AI Use Case Inventory
Risk & Policy Workflows
AI Model Deployment
Evidence for Audits
Policy-level only
Bias & Drift Monitoring
Model Explainability
EU AI Act Alignment
Policy-level only
Stakeholder Dashboards
Governance & policy focus 

Already using Credo AI?

Here’s how Deeploy can work with, or simplify, your current stack.

Complement Credo AI

Keep using Credo AI for policy frameworks and risk cataloging. Add Deeploy for technical model governance:

Replace Credo AI entirely

Deeploy offers most Credo AI functionalities PLUS model-level control and monitoring:

Why teams switch from Credo AI to Deeploy

Model-level depth

Credo AI catalogs AI at the policy level. Deeploy monitors bias, drift, and explainability at the model level, generating regulator-ready logs that prove compliance.

Operational governance

Policy frameworks in Credo AI stay as documentation. Deeploy takes those policies and maps them to operational controls, automated checks applied directly to models in production.

Bridging governance & technical teams

Compliance officers see policy alignment. Data scientists see model performance. Engineering sees deployment metrics. One platform, three critical perspectives.

Deeploy adds the governance infrastructure your AI stack has been missing

Centralise and govern all AI activity with a unified registry that captures every model and use case across your organisation, from in-house developments to vendor solutions, ensuring nothing goes into production without proper oversight.

Implement comprehensive governance across teams with built-in frameworks like the EU AI ActISO/IEC 42001, and NIST AI RMF or create custom frameworks tailored to your organisation’s specific requirements.

Classify any AI use case instantly with the built-in EU AI Act risk classification assessment, and know exactly which controls apply to your use case.

Maintain complete transparency and compliance with automatic logging that records every action, ensuring full traceability across your system.

Build authorisation workflows with approval rules that distribute responsibility across teams, requiring sign-off for new use cases, models and updates.

Monitor AI performance with real-time tracking. Detect issues early and ensure your models remain compliant, accurate, and reliable.

Ready to see model-level AI governance in action?

Trusted by organisations running AI at scale

Frequently asked questions

What's the main difference between Credo AI and Deeploy?

Credo AI focuses on policy frameworks and governance workflows, helping you catalog AI use cases, assess risks, and align with governance standards.

Deeploy delivers policy frameworks AND operational governance. Use case inventory and risk workflows, plus model-level controls that enforce those policies in production. Map governance requirements to automated checks, monitor models for bias and drift, generate explainability for every prediction, and produce automatic audit trails.

Credo AI catalogs your AI use cases and manages governance policies. But it doesn’t monitor what your models actually do in production and can’t map policy requirements directly to model controls.

The gap:

  • Credo AI tells you what policies you should follow
  • Deeploy proves you’re actually following them with technical evidence

Common scenario: You document a bias monitoring policy in Credo AI. Great. But who’s actually monitoring for bias? What happens when drift occurs? Can you show regulators the evidence?

Your options:

  1. Complement Credo AI: Keep it for policy frameworks, add Deeploy for technical monitoring & governance controls. You can import generated reports onto Credo AI. 
  2. Consolidate to Deeploy: Deeploy provides you with policy frameworks + technical governance in one platform. All teams in one place. Regulatory ready. 

For most organisations, yes.

What Deeploy includes from Credo AI’s core:

✅ AI system inventory

✅ Risk classification workflows

✅ EU AI Act, ISO 42001, NIST frameworks

✅ Compliance documentation

✅ Approval workflows

✅ Stakeholder dashboards

What Deeploy adds that Credo AI doesn’t have:

✅ Real-time technical controls

✅ Audit trails 

✅ Model deployment capability

✅ Model explainability

✅ Bias & drift monitoring

Bottom line: If you need governance frameworks + technical evidence (which most regulated organisations do), Deeploy delivers both. If you only need policy documentation without operational monitoring, Credo AI might suffice, but that’s increasingly insufficient for regulators.

Yes, for most common governance artifacts:

What can be imported:

✅ AI use case inventory

✅ Risk classifications

✅ Policy documentation

✅ Governance & compliance requirements

✅ Stakeholder roles

What you gain in migration:

  • Everything you had in Credo AI (policy layer)
  • Plus everything you didn’t have (technical layer)
  • Unified platform for governance + engineering teams

Credo AI:

✅ Policy frameworks aligned to EU AI Act

✅ Documentation templates

❌ No technical controls (Article 15 – accuracy, robustness)

❌ No operational monitoring

Deeploy:

✅ Policy frameworks aligned to EU AI Act

✅ Documentation templates

Technical controls (accuracy monitoring, robustness testing)

Operational evidence (audit logs, explainability, traceability)

Key difference: EU AI Act requires both policy compliance AND technical controls. Credo AI handles policy. Deeploy handles both.

Built in Europe: Deeploy is headquartered in The Netherlands, designed from day one for European compliance requirements and data sovereignty needs.

Comprehensive technical evidence that satisfies auditors:

Audit trail evidence:

  • Per-prediction logs with timestamps
  • Complete input/output records
  • Explainability outputs for individual decisions
  • User actions and human oversight records

Performance evidence:

  • Bias metrics across demographic groups
  • Model accuracy over time
  • Drift detection history
  • Fairness assessments

Governance evidence:

  • Control compliance status
  • Approval workflows and attestations
  • Risk classifications and justifications
  • Documentation (model cards, data cards, policies)

Export capabilities:

  • PDF reports for regulators
  • Real-time dashboards for live audits

Yes. Deeploy is built for integration.

Native integrations:

✅ Cloud platforms: AWS, GCP, Azure

✅ MLOps tools: MLflow, Kubeflow, SageMaker

✅ Model stores: HuggingFace, your internal registries

✅ LLM providers: OpenAI, Mistral, Anthropic

✅ Data warehouses: Snowflake, Databricks, BigQuery

✅ Open-source frameworks: Triton, PyTorch, Hugging Face, XGBoost.

✅ Webhooks & slack integration for alerts and events

Your ML stack is already complex. Deeploy complements it with a strong governance layer rather than forcing you to change everything.

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Build audit-ready AI governance from day one