Holistic AI helps organisations assess AI risk and align governance frameworks. Deeploy combines governance, deployment, monitoring, and controls in a single platform where AI models actually run.
Your governance team uses Holistic AI to manage AI inventories, conduct impact assessments, and document compliance requirements. But there’s a fundamental challenge:
The governance platform sits separately from the AI systems it’s governing.
When a governance control needs to be enforced, monitored, or audited, you depend on engineering teams, external tooling, and manual processes to prove it happened.
Holistic AI governs AI systems from the governance layer. Deeploy governs AI systems from the governance layer and the model layer.
(What Deeploy & Holistic AI do)
(What only Deeploy does)
Holistic AI helps you track governance on paper. Deeploy turns it into real, operational controls.
Here’s how Deeploy can work with, or simplify, your current stack.
Keep Holistic AI for governance workflows and assessments. Add Deeploy for technical model governance:
Deeploy offers most Holistic AI functionalities PLUS model-level control and monitoring:
Bottom Line: Holistic AI helps you govern AI systems. Deeploy lets you govern, deploy, monitor, and prove compliance from the same platform where AI models run.
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.
Monitor and govern AI agents from a single platform, with full visibility into agent behaviour, tool usage, and decision flows. Apply governance controls and maintain audit-ready records as agents operate in production.
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.
Holistic 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.
Holistic AI helps organisations establish governance processes through AI inventories, impact assessments, policy frameworks, and compliance reporting.
Deeploy addresses a different challenge: governing AI systems directly where they are deployed and operating in production.
Because AI models run directly on Deeploy, the platform can continuously monitor model behaviour, apply governance controls, generate audit evidence, and provide explainability at the model level.
Common scenario: You document a bias monitoring policy in Holistic 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 Holistic AI’s core:
AI system inventory
Risk classification workflows
Compliance documentation
Approval workflows
Stakeholder dashboards
What Deeploy adds that Holistic AI doesn’t have:
EU AI Act, ISO 42001, NIST control frameworks
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, Holistic AI might suffice, but that’s increasingly insufficient for regulators.
Not necessarily. Some organisations use both platforms because they serve different purposes.
Holistic AI can be used to manage governance frameworks, assessments, and reporting.
Deeploy can be used to deploy AI systems, monitor model behaviour, enforce governance controls, and generate technical evidence.
For organisations with mature governance programs already built around Holistic AI, Deeploy often serves as the operational layer that extends governance into production AI systems.
For organisations evaluating new platforms, Deeploy can often cover both governance and operational governance requirements within a single environment.
Both platforms support organisations preparing for the EU AI Act. The difference is in how compliance is demonstrated.
Holistic AI primarily focuses on governance processes, assessments, documentation, and compliance readiness.
Deeploy focuses on operational compliance.
Because AI systems are deployed and monitored directly within Deeploy, organisations can generate the technical evidence regulators increasingly expect, including:
In practice, governance documentation alone is often not sufficient during audits. Organisations also need evidence showing how controls were implemented and maintained over time.
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.
