Compare AI governance platforms for
shadow AI, DLP, and compliance
16 stack-by-stack comparisons to help enterprise security and compliance teams choose the right AI governance platform. See where Zscaler, Microsoft Purview, Nightfall, Harmonic Security, CrowdStrike, and others stop, and where AI governance starts.
Pick the stack you already own
Most CISOs are not asking "what is the best AI governance vendor." They are asking "do I need one if I already have these tools." Pick the closest match.
You catch network-level traffic. Aona adds the browser layer your SSE cannot reach.
Purview governs data inside the M365 estate. AI tools live outside it.
DLP scans for sensitive data. Governance scans for risky AI behaviour.
Data security posture stops at the data layer. AI usage starts where DSPM ends.
EDR watches the endpoint. AI usage happens above it, in the browser.
Cloud posture manages your infrastructure. AI risk is a human-layer problem.
GRC documents policy. Aona enforces it at the moment of action.
Comparing pure-play AI security platforms. Here is how Aona stacks up.
Where every layer of your stack stops, and where AI governance starts
One matrix. Seven stack categories you may already own, eight controls that AI risk requires. Print it, paste it into a board memo, or use it to score your own gaps.
| Control | SSESecure Service EdgeZscaler, Netskope, Palo Alto | DLPData Loss PreventionNightfall, Polymer, Symantec | EDREndpoint DetectionCrowdStrike, SentinelOne | CASBCloud Access BrokerNetskope CASB, MS Defender for Cloud Apps | PurviewMicrosoft 365 governancePurview, Defender, Entra | IAMIdentity & AccessOkta, Entra ID, Ping | AonaBrowser pluginChrome, Edge, Firefox | AonaNative endpoint appWindows + macOS |
|---|---|---|---|---|---|---|---|---|
| Discover | ||||||||
Shadow AI app discovery Which AI tools are employees using | ||||||||
Per-prompt content classification What data is sent to the model | ||||||||
Native desktop AI app interception ChatGPT, Copilot, Claude desktop apps | ||||||||
AI agent inspection Process, network, MCP server discovery | ||||||||
Off-network and BYOD coverage Personal devices, unmanaged endpoints | ||||||||
| Govern | ||||||||
Real-time user coaching Inline guidance at the moment of action | ||||||||
AI-specific policy templates Acceptable use, model allowlist, data classes | ||||||||
Policy violation trend reporting Per team, per tool, over time | ||||||||
| Protect | ||||||||
Block unsanctioned AI apps At the network, the page, or the prompt | ||||||||
Inline prompt redaction Strip PII or secrets before they hit the model | ||||||||
Layout-preserving file redaction DOCX and Excel uploads kept readable after redaction | ||||||||
Where do you sit on this map?
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Choose the comparison that matches your current stack
Most buyers do not replace an entire security stack. They need to know which AI governance gap remains after their existing tools do their job. These routes help security, compliance, and IT teams compare Aona against the products they already own or are evaluating.
Aona vs Microsoft Purview
Compare Microsoft 365 data governance with browser-level prompt coaching, shadow AI discovery, and AI usage evidence.
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SSE / SASEAona vs Zscaler
See where network-level SSE app visibility stops and workforce AI governance starts. Covers the Zscaler AI Security Suite.
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AI-nativeAona vs Harmonic Security
Both are AI-native platforms. Compare by stack fit, geography, trial path, and endpoint coverage depth.
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AI-nativeAona vs Prompt Security
Evaluate prompt visibility, coaching, employee behaviour change, and governance reporting side by side.
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AI-nativeAona vs WitnessAI
Compare endpoint coverage across browser, native desktop, and agent against network-layer AI visibility.
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Cloud DLPAona vs Nightfall AI
Nightfall covers SaaS DLP broadly. See how endpoint AI governance complements its API-based connectors.
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Cloud DLPAona vs Polymer
Polymer governs SaaS collaboration apps. Aona governs AI tools on the endpoint. Complementary layers.
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DSPMAona vs Varonis
Varonis governs your data at rest. Aona governs what employees do with that data in AI tools.
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DSPMAona vs Cyberhaven
Cyberhaven traces data lineage. Aona intercepts AI usage at the endpoint before data leaves.
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DSPMAona vs Metomic
Metomic governs data inside SaaS apps. Aona adds the AI usage control layer on top.
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EDRAona vs CrowdStrike
Falcon AIDR adds AI detection to EDR. Aona is purpose-built Workforce AI Security from the ground up.
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CSPMAona vs Wiz
Wiz secures cloud AI infrastructure. Aona governs the people using AI tools on managed endpoints.
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GRCAona vs OneTrust
OneTrust is your GRC system of record. Aona enforces AI policy at the moment of employee action.
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AI-nativeAona vs Lakera
Lakera secures AI you build. Aona governs AI your employees use. Different problems, complementary layers.
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ConceptAI governance vs DLP
Understand why traditional DLP is necessary but not sufficient for browser prompts, AI tools, and agent workflows.
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ToolFind your fit quiz
Answer a few stack questions and route security, compliance, or IT buyers to the most relevant comparison.
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What is an AI governance platform?
An AI governance platform is enterprise software that gives security and compliance teams visibility and control over how employees use AI tools, tools like ChatGPT, Claude, Microsoft Copilot, Gemini, and hundreds of others that live outside traditional security controls.
Traditional tools were not designed for this surface. DLP scans for sensitive data at file egress, not at the moment an employee types a customer record into a chat window. SSE platforms like Zscaler see which AI domains are being accessed at the network layer, but cannot see the content of what is typed. Microsoft Purview governs the Microsoft 365 estate, not third-party AI tools. EDR platforms watch the operating system, not the browser tab where AI usage happens.
A purpose-built AI governance platform fills four gaps: shadow AI discovery (finding AI tools IT does not know about), prompt-level DLP (blocking sensitive data before it reaches an AI model), real-time employee coaching at the moment of risk, and compliance reporting that maps to frameworks like the EU AI Act and ISO 42001. These are not features that can be bolted onto legacy tools, they require an agent or plugin that sits between the employee and the AI tool, at the browser or native app layer.
Use the comparisons above to see exactly where your current stack stops and where an AI governance solution starts. Run the stack quiz to get a personalised recommendation.
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