Which one do I need for the EU AI Act?

It depends on your role. If you provide or deploy high-risk AI systems, you need runtime oversight of the kind Deeploy offers. Every employer using AI tools also has literacy and usage-governance duties — that’s DocsOrb’s territory, and for most SMBs it’s the obligation that arrives first.

Can DocsOrb monitor the models we deploy in production?

No. DocsOrb doesn’t do model monitoring, drift detection, or explainability. If you run production models, pair DocsOrb with an MLOps or model-governance tool.

Can we use both together?

Yes. A common split: engineering governs deployed systems in Deeploy, while compliance governs workplace AI use, policies, and acknowledgment evidence in DocsOrb.

DocsOrb vs Deeploy

Deeploy governs the AI systems you build and run: model registries, runtime monitoring, drift detection, explainability, and control frameworks like ISO 42001 for high-risk systems. DocsOrb governs the AI your employees use: policies, approved tools, acknowledgments, browser guardrails, and audit evidence. They answer different questions — “is our model behaving?” versus “is our workforce using AI within the rules?” Some organizations genuinely need both.

Employee AI usePolicy to guardrailsNo GRC overhead

What each product covers

Capability	DocsOrb	Deeploy
Primary job	Govern employee AI use — from policy to enforcement to evidence	Govern AI systems and agents you deploy — runtime monitoring and control
Typical owner	Compliance, legal, HR, risk, and security teams	ML engineering, data science, and model risk teams
AI discovery	Shadow AI discovery across workplace tools and browsers	AI system discovery across MLOps and GenAI platforms
Policy lifecycle & acknowledgments	Yes — authoring, approvals, employee portal, acknowledgment campaigns, training	Not the focus — governance workflows target AI systems, not employee policy rollout
Runtime model monitoring & explainability	No — DocsOrb doesn’t monitor models you deploy	Yes — core strength: drift detection, performance alerts, explainers, tracing
Guardrails	Browser and MCP guardrails on employee AI use, linked to published policies	Runtime guardrails and tracing for deployed LLMs and agents
Framework alignment	EU AI Act posture, AI literacy, acknowledgment and enforcement evidence	ISO 42001 and NIST AI RMF control frameworks, high-risk system oversight
Best for	SMBs and mid-market teams governing workplace AI without enterprise GRC overhead	Organizations deploying their own AI systems, often high-risk under the EU AI Act

This comparison is based on publicly available information as of August 2026 and is reviewed regularly. All trademarks belong to their respective owners. Spotted something outdated or inaccurate? Contact us and we’ll fix it.

Which one fits your team?

Choose DocsOrb if…

Your AI risk is employees using third-party AI tools, not models you built
Compliance, legal, HR, or security owns the program
You need policies, acknowledgments, training, and evidence in one workflow
You want governance running in days, without an enterprise implementation

Choose Deeploy if…

You build and deploy your own models, LLM applications, or agents
You operate high-risk AI systems that need runtime oversight and explainability
Your governance program is led by engineering and data science

Frequently asked questions

Less than it appears. Deeploy is strongest at technical governance of AI systems you deploy; DocsOrb is built for governing employee AI use. Many organizations need employee-AI governance first — it’s where most day-one exposure sits.

Govern the AI your people use every day.

DocsOrb covers the workforce side of AI governance: policy, approved tools, guardrails, and audit evidence — sized for teams without a governance department.

DocsOrb

DocsOrb brings the policy, rollout, training, acknowledgment, and evidence work into one system once the manual process becomes too expensive to maintain.

Key features include:

Employee AI use

Policy to guardrails

No GRC overhead

More comparisons

All comparisons