Last updated: June 2026.

A large transportation and logistics company used Aurascape to get organization-wide visibility and control over AI use quickly. It went from proof of value to full deployment in about six weeks, started with 400 users on the first day and expanded to a 2,000-user rollout, with sensitive-data interactions monitored across all deployed users.

Most organizations do not have that visibility. Cisco found that 60 percent of organizations cannot see the specific prompts and requests employees send to AI tools (Cisco Cybersecurity Readiness Index, 2025). This company set out to close that gap fast, before AI use spread further than it could see.

This transportation AI security case study walks through how the company moved so quickly, the architecture it deployed, and the results that followed.

Getting ahead of AI use without a long deployment

AI use was spreading across the company. Employees were trying new tools, and the pace was faster than anyone could track by hand. Leadership wanted to get ahead of it with organization-wide visibility and control, not in a year, but quickly, before the gap widened. The problem was twofold. The company’s existing security stack was built for web and SaaS traffic and could see destinations, not the AI interactions happening inside them. And standing up a new control usually means a long deployment, which would leave AI use unseen for months while the project ran.

Speed mattered for a second reason. AI adoption is nearly universal, but McKinsey found that nearly two-thirds of organizations have not yet begun scaling AI across the enterprise (McKinsey, 2025). This company wanted to move from scattered, unseen AI use to a governed, organization-wide program, and it did not want the security work to be the thing that held that progress back.

What the team wanted	Why it is hard with legacy approaches	What Aurascape provides
Organization-wide visibility into AI use, quickly	Legacy tools take a long deployment and still see only destinations, not the AI interactions happening inside them.	Fast deployment that delivers organization-wide visibility into AI use in weeks.
Proof of value before a full rollout	A proof of value that drags on delays both the decision and the protection.	A proof of value that stands up quickly and expands to the whole organization without re-architecting.
Sensitive-data use monitored across everyone	Partial coverage leaves blind spots that grow as AI use spreads.	Monitoring of sensitive-data interactions across all deployed users, with context-aware policy.

Phase one: discover AI use across the organization

Aurascape started by discovering AI use across the company. It found both well-known and long-tail AI applications, including AI embedded in SaaS products that employees were already using (Aurascape, 2026). It recognized brand-new AI applications and agents quickly and risk-scored them based on behavior, permissions, and data handling, so the security team had a single, current view of which AI tools were in use and how risky each one was.

That view arrived fast. Within the first weeks, the company had organization-wide visibility into AI use (Aurascape, 2026), which is what turned a proof of value into a decision to roll out.

Phase two: control AI use in context

Visibility set up control. Aurascape applied policy based on the full context of each interaction, not just the destination, accounting for the user, whether a session used a sanctioned enterprise tenant or a personal account, the application and mode in use, and the data involved (Aurascape, 2026). Security teams could allow, coach, warn, block, or redact based on the interaction itself, and coach employees in real time when an action needed it, rather than relying on a blunt allow-or-block decision.

Phase three: protect and monitor sensitive data

As the rollout expanded, Aurascape protected sensitive data in real time. It used multimodal classifiers to identify sensitive data, including customer records, operational data, and other proprietary business information, as it moved through AI interactions (Aurascape, 2026). When an interaction involved sensitive data, Aurascape could redact it inline or block the action, and it monitored sensitive-data interactions across all deployed users, so coverage did not lag behind the rollout.

Aurascape kept interaction records for audit and effectiveness, governed by role-based access control (RBAC) so that only the right roles could see them. That gave the company a clear, auditable view of how AI was being used and how its controls were performing, without creating a new privacy concern of its own.

The results

Deploying Aurascape produced fast, measurable results:

Metric	Result
Proof of value to full deployment	About six weeks
Users on day one	400
Full rollout	2,000 users
AI use visibility	Organization-wide
Sensitive-data interactions monitored	Across 100 percent of deployed users

The pattern is speed without shortcuts. The company reached organization-wide visibility and active data protection in about the time many security projects spend in planning. Because the proof of value expanded into a full rollout without re-architecting, protection kept pace with adoption, and sensitive data stayed protected as more users came online.

Why fast time to value matters

The case for moving fast is simple. AI use grows every week, and the visibility gap grows with it. When most organizations cannot see the prompts employees send and most have not yet scaled AI with the controls to match, the organizations that get visibility and control early are the ones that can adopt AI broadly with confidence. Aurascape was built to understand AI interactions, which is what lets it deliver that visibility quickly and run alongside the existing security stack, additive to whatever secure access or data protection tools are already in place (Aurascape, 2026).

Fast visibility is not only about finding shadow AI. Aurascape governs sanctioned, licensed tools with the same context, using Intentions and entitlement to control what a user can do inside an approved application, not just whether they can reach it (Aurascape, 2026). For an operations-heavy business, that means it can open up the AI it has chosen quickly, and keep granular control as use grows.

Frequently asked questions

How fast can Aurascape be deployed?

Quickly. In this deployment, a large transportation and logistics company went from proof of value to full deployment in about six weeks, starting with 400 users on the first day and expanding to a 2,000-user rollout. The proof of value expanded into the full rollout without re-architecting, so the timeline reflected real coverage, not a limited pilot.

What does organization-wide AI visibility include?

It includes discovery of the AI tools in use, both well-known applications and the long tail, along with AI embedded in SaaS products. Aurascape risk-scores each tool based on behavior, permissions, and data handling, and shows who is using what, so security teams have a single, current view of AI use across the organization rather than a list that is always out of date.

How does Aurascape monitor sensitive-data use?

Aurascape uses multimodal classifiers to identify sensitive data, including customer records and operational data, as it moves through AI interactions. When an interaction involves sensitive data, Aurascape can redact it inline or block the action, and it monitors sensitive-data interactions across all deployed users. Interaction records are kept for audit and effectiveness, governed by role-based access control for privacy.

Does Aurascape replace our existing security tools?

No. Aurascape is additive. It runs alongside the secure access, data protection, and web security tools an organization already has, and focuses on the AI interactions and agent execution those tools were not designed to understand (Aurascape, 2026). That is part of why it deploys quickly: it adds AI visibility and control without a rip-and-replace project.

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Aurascape gives organizations visibility and control over AI use quickly, so security keeps pace with how fast AI is spreading. By discovering the AI tools in use, understanding each interaction in context, and protecting sensitive data inline, it turns AI visibility from a long project into a fast, organization-wide result.

See how quickly Aurascape can give you organization-wide AI visibility →