Credo AI governs policies. Deeploy governs models, with controls, real-time monitoring, and technical evidence that proves compliance.
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?
(What Deeploy & Credo AI do)
(What only Deeploy does)
Credo AI helps you track compliance on paper. Deeploy turns it into real, operational controls.
Here’s how Deeploy can work with, or simplify, your current stack.
Keep using Credo AI for policy frameworks and risk cataloging. Add Deeploy for technical model governance:
Deeploy offers most Credo AI functionalities PLUS model-level control and monitoring:
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 Act, ISO/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.













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:
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:
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:
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:
Performance evidence:
Governance evidence:
Export capabilities:
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.
Build audit-ready AI governance from day one