The Agentic AI and SaaS Visibility Gap

Today's converged AI and SaaS ecosystem is full of blind spots.

Security teams can’t see how sensitive data moves across SaaS and AI apps, the identities involved, and if there are any indicators of compromise.

Core Problems

Can't see how AI agents and integrations move data.

Vendor breaches expose sensitive data with no way to scope impact fast.

SecOps workflows don't cover the agentic attack surface.

SaaS and AI security are fragmented across scattered tools.

The result?

Security teams can't identify or quickly respond to threats like OAuth token abuse, data exfiltration, or third party integrations accessing data they shouldn't.

Can't see how AI agents and integrations move data.

Vendor breaches expose sensitive data with no way to scope impact fast.

SecOps workflows don't cover the agentic attack surface.

SaaS and AI security are fragmented across scattered tools.

The result?

Security teams can't identify or quickly respond to threats like OAuth token abuse, data exfiltration, or third party integrations accessing data they shouldn't.

Enterprises need an agentic ecosystem security platform that automatically maps sensitive data flows, identifies risky connections, and provides clear remediation guidance without adding operational complexity.

Vorlon complements "front door" tools by protecting the "engine room," the AI-driven execution layer where agents, SaaS apps, and integrations intersect with sensitive data.

Legacy SSPM tools check configurations, but miss data in motion between SaaS and AI apps and connected services.

SIEMs lack SaaS and Agentic AI context and require tedious maintenance, leaving gaps unaddressed.

DSPM solutions track data at rest, but lose visibility once information flows through APIs to third parties.

SASE/CASB solutions enforce policy on user-to-app traffic but struggle with backend SaaS-to-SaaS, SaaS-to-AI, and integration-layer traffic.

Legacy SSPM tools check configurations, but miss data in motion between SaaS and AI apps and connected services.

SIEMs lack SaaS and Agentic AI context and require tedious maintenance, leaving gaps unaddressed.

DSPM solutions track data at rest, but lose visibility once information flows through APIs to third parties.

SASE/CASB solutions enforce policy on user-to-app traffic but struggle with backend SaaS-to-SaaS, SaaS-to-AI, and integration-layer traffic.

The new risk isn't just at the edge but within the backend ecosystem.

AI agents execute millions of high-speed operations.

Agents move data between apps via APIs and MCP servers.

Agents operate with excessive permissions and unchecked autonomy.

Static permission checks can't detect when an agent starts behaving like an attacker.

Proxies introduce latency that breaks high-frequency, agentic workflows.

Browser extensions miss the backend machine-to-machine traffic that defines agentic workflows.

AI agents execute millions of high-speed operations.

Agents move data between apps via APIs and MCP servers.

Agents operate with excessive permissions and unchecked autonomy.

Static permission checks can't detect when an agent starts behaving like an attacker.

Proxies introduce latency that breaks high-frequency, agentic workflows.

Browser extensions miss the backend machine-to-machine traffic that defines agentic workflows.

When you can see the whole picture — how sensitive data moves, who (or what) is accessing it, and what they’re doing — you can proactively secure your agentic ecosystem.

The New Approach

See how you can deploy AI at scale while protecting your most sensitive data.

See the New Approach

The Agentic AI and SaaS Visibility Gap

Today's converged AI and SaaS ecosystem is full of blind spots.

Core Problems

The result?

The result?

Enterprises need an agentic ecosystem security platform that automatically maps sensitive data flows, identifies risky connections, and provides clear remediation guidance without adding operational complexity.

Vorlon complements "front door" tools by protecting the "engine room," the AI-driven execution layer where agents, SaaS apps, and integrations intersect with sensitive data.

The new risk isn't just at the edge but within the backend ecosystem.

When you can see the whole picture — how sensitive data moves, who (or what) is accessing it, and what they’re doing — you can proactively secure your agentic ecosystem.

See how you can deploy AI at scale while protecting your most sensitive data.

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