Aurascape vs Zscaler

Both platforms help enterprises secure AI usage and apply real-time controls. The difference is whether AI security is at the network layer and depends on existing SSE/SASE proxy architecture, or if AI security is purpose-built to provide control for all AI activity. This comparison is built for CISOs and enterprise security teams evaluating Zscaler alternatives for AI security.

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Compare the Aurascape AI Security Platform to Zscaler

Zscaler and Aurascape take different architectural approaches to AI security. Here are the key differences that matter for enterprise buyers, CISOs, and Fortune 500 security teams.

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Aurascape

Zscaler

AI-native platform architecture
Aurascape
Purpose-built AI interaction layer that decodes AI traffic natively across WebSockets, Protobuf, JSON, RPC, APIs, MCP and more. Visibility and control are properties of the architecture, not features layered onto an existing proxy.

Zscaler

AI security delivered through the Zero Trust Exchange cloud proxy. Inspection depth depends on URL and domain identification, which can be limited for AI-specific protocols and traffic patterns that don't resemble traditional HTTP/HTTPS web traffic.
AI discovery and risk intelligence
Aurascape
Discovers tens of thousands of AI applications automatically, with deep traffic decoding support for thousands, across chatbots, IDEs, agents, LLMs, and MCP servers. New apps added on a 48-hour SLA. Risk scoring uses 30+ AI-native attributes including data retention, model training behavior, privacy posture, and known vulnerabilities, refreshed continuously rather than treated as static categories.

Zscaler

AI app discovery extends existing CASB shadow IT framework, mapped to URL categories such as "AI and ML Applications." Risk scoring follows the SaaS application model, so attributes are not clearly relevant for AI tools, with depth of assessment varying by application popularity and the manual vendor research for that specific tool.
Coverage across AI surfaces
Aurascape
Consistent policy enforcement across surfaces: browsers, embedded AI inside SaaS apps and trusted websites, desktop AI clients including Claude Desktop and Cursor, CLI tools, IDEs, and local agents like Claude Code and OpenClaw. Granular interaction-level policy allows controlling embedded AI features without blocking the parent app.

Zscaler

Additional surface coverage for specific AI tools when AI Guard is integrated with ZIA. Embedded AI within trusted SaaS apps and websites is governed at the parent-app or URL level rather than at the AI-feature level.
MCP and agentic governance
Aurascape
Zero-bypass MCP Gateway in general availability. Controls MCP connections and tool calls inline, with data-lineage tracking across cross-system action chains. Detects unsanctioned MCP clients reaching internal MCP servers and applies policy at the tool-call level, not just at the network or connection level.

Zscaler

An MCP Gateway was announced in January 2026 as part of the AI Security Suite launch. Public documentation on capabilities, controls, and customer availability is limited. Depth of MCP visibility and tool-call governance is unclear and may be roadmap for some customers.
Conversation intelligence
Aurascape
End-to-end conversation intelligence: prompts and responses correlated as a single conversation session with session continuity across hundreds of chatbots, IDEs, agents, and MCP tools. Real-time policy enforcement with user coaching at the moment of action. Conversation visibility governed by RBAC so admins see only what their role allows.

Zscaler

AI Access Security captures prompts for a defined set of supported applications. Response inspection is available through AI Guard, a separate offering focused on inline LLM threat detection and DLP. Stitching prompts, responses, file uploads, and session data into a continuous conversation record across the long tail of AI tools is not part of the published feature set.
Policy precision
Aurascape
Policy can act on data, threat, identity, entitlement, app risk, in-tool intent, and individual tool calls. Actions include block, redact, warn, coach, allow-with-flag, and precision interventions such as redirecting Copilot free-tier users to the enterprise license or preventing OneDrive content from being sent to ChatGPT for training.

Zscaler

Policy actions follow the established CASB pattern (allow, block, isolate, coach) applied to AI URL categories and supported AI applications. License-tier-aware actions (e.g., redirecting users to enterprise license) and tool-call-level policy are not part of the published feature set.
Data Protection
Aurascape
Data classification covers 600+ AI categories using transformer-based models, with multimodal inspection across text, images, and audio. Custom data categories and fingerprinting supported.

Zscaler

AI-powered data classification was added in 2025 with 200+ document categories; modality coverage is primarily text and powered by OCR.

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Why Customers Choose Aurascape Over Zscaler

A comparison across key enterprise AI security dimensions for CISOs and security architects.

Aurascape approach

Zscaler

Architecture

AI-native interaction layer

Purpose-built to govern AI interactions: prompts, responses, actions, and agent behavior across all enterprise AI surfaces. AI coverage is a property of the architecture rather than an extension of pre-AI security infrastructure.

Zscaler

SSE/SASE proxy architecture

AI security capabilities run on the Zero Trust Exchange cloud proxy. Depth of AI governance follows the depth of application-specific support, which is added on a per-app basis as the AI landscape evolves.

Coverage across AI surfaces

Consistent coverage across all AI surfaces

Prompt and response visibility, policy enforcement, and granular interaction-level policy apply consistently to new commercial AI apps, embedded AI inside SaaS apps and websites, desktop AI clients, CLI tools, IDEs, and local agents including Claude Code and OpenClaw.

Zscaler

Expanding coverage, with SaaS-era depth of control

Embedded AI inside SaaS apps and desktop AI clients that don't traverse the cloud proxy can fall outside the inspection path. New AI protocols and traffic patterns may require add-on support before they are fully governed. Full governance still means SaaS-level controls, not AI-era decoding and granular policy options.

How they solve enterprise AI security challenges today

Full AI interaction governance, built for how AI works

Aurascape delivers workforce AI governance and built AI guardrails as one platform, with policy enforcement that follows the AI interaction wherever it occurs. Legacy AppIDs identify domains or basic actions only. Aurascape maps AI traffic profile. No decryption gaps, no weeks-long lag to find and support new AI apps and agents.

Zscaler

AI lifecycle focus, with architecture-dependent enforcement

Policy outcomes for workforce AI usage depend on speed-to-support. Acquisitions and roadmap appear to favor buildtime AI security.

Our Customers

microage
usxpress
usc
iihs
thepolicecu
typeoneenergy
powerlatticeinc
eventussecurity
ackway
sitime
winwire
zooberpay
peckhannafordbriggs
auradine
upscaleai
sailinternet
s3ntrycorp
actransit

Why CISOs and Enterprise Security Teams Choose Aurascape

A dedicated AI-native control layer for the full enterprise AI ecosystem, designed for Fortune 500 environments and growing enterprises alike.

Govern AI usage with clarity

See how employees use commercial AI, embedded AI, copilots, and agents across the enterprise, then apply policy with precision, not just coarse blocking.

Secure AI systems across build & use

Extend coverage from employee AI use cases into the AI systems your teams build, deploy, and operate. One platform for the full lifecycle.

Control agentic interactions

Apply guardrails across agentic activity to protect sensitive data, prevent threats, and monitor built, bought, and shadow AI agents.

Built for real enterprise AI

Govern AI wherever work happens: browsers, desktop apps, SaaS tools, CLI tools, IDEs, and agentic workflows. Additive to your existing security stack.

See how Aurascape compares in your environment

Bring your top comparison criteria. We'll show Aurascape in the context of your real AI surfaces, policies, and rollout goals, with examples relevant to your enterprise environment.

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