Docs
Book a demo
AI Agent

How a Fortune 100 Giant Put Secure Guardrails on its AI—Without Slowing It Down

See how a Fortune 100 leader put guardrails on multi-agent AI—enforcing zero-trust data policies, retaining AI reasoning, and meeting GDPR compliance without added latency.
100%
Compliance Achieved

Get the full case study

We email the PDF to your work inbox, so you can forward it to your team.

By submitting you agree to Protecto’s privacy policy.

100%
Regulatory Compliance Achieved
1 week
Time to implement enterprise-wide AI security
Zero
Performance Latency in AI Workflows

The challenge

Securing Autonomous AI in a Complex Enterprise Environment

A Fortune 100 technology leader needed to implement robust security measures for their next-generation AI infrastructure powered by multi-agent architectures. As their autonomous AI agents began reading, interpreting, and acting on enterprise data across multiple departments, they faced critical security and compliance challenges.

  • Sensitive data flowing through agent chains requiring protection across documents, logs, emails, and support tickets
  • Global regulatory compliance requirements including GDPR and data residency restrictions
  • Need to preserve AI reasoning capabilities while protecting sensitive information
  • Role-based access control requirements varying by team and function
  • Enterprise integration demands with existing Active Directory and orchestration pipelines
AI Agent

The key win was that we didn't need to rewire anything—we plugged Protecto into our existing planner and AD stack and started enforcing real-time data policies within days.

100%
Compliance Achieved
Director of AI Platform, Fortune 100 Tech Company
The solution

Policy Enforcement for AI with Protecto Vault

Protecto Vault was deployed as the core enforcement layer in the company’s AI architecture, serving as the policy and control plane for sensitive data handling.

01

Context-Aware Masking

  • Automatically identifies and tokenizes sensitive data without breaking semantic meaning
  • Preserves AI understanding and reasoning capabilities while protecting information
  • Maintains the context necessary for accurate LLM outputs
02

Policy-Based Unmasking

  • Grants access only to users or agents with proper authorization based on AD roles
  • Enforces contextual permissions that respect data access policies
  • Enables fine-grained control over what data can be revealed and when
03

Zero-Trust Architecture

  • Implements “lock-by-default” approach aligned with zero-trust principles
  • Inspects, evaluates, and masks every AI prompt in real-time
  • Ensures data is only exposed when policy, identity, and context allow it
04

Want the full story? Get the case study PDF in your inbox and share it with your team.

Get the case study

The results

Enterprise-Grade AI Security Without Sacrificing Performance

By integrating Protecto Vault, the Fortune 100 company created a secure foundation for its agentic architecture—ensuring AI could act autonomously while staying compliant and trustworthy.

Key achievements

  • Full regulatory compliance with data residency, GDPR, and internal security requirements
  • Preserved AI reasoning capabilities by retaining semantic meaning in masked data
  • Real-time role-based access control tied directly to existing AD roles
  • Zero-trust at inference time without introducing latency
  • Comprehensive audit logging for all data access and masking actions
  • Seamless integration with existing enterprise systems and workflows

More case studies

Browse all case studies

API
Detection and masking for telemetry
Enterprise cloud and software

Protecting Sensitive Telemetry for AI and Analytics

A large technology company wanted to use operational telemetry and partner data for internal AI, analytics and model improvement. Customer identifiers and other sensitive fields complicated the use of raw data.
Read the case study
99%
Recall on sensitive data, incl. Arabic
Banking

How Bank Muscat kept customer data in the bank while adopting Gemini

Bank Muscat let employees use Gemini while customer data stayed under the bank’s control. Protecto found sensitive values in Arabic and English with 99% recall, and the proof of concept worked in four weeks.
Read the case study
13M
Long-form texts processed daily
SaaS

Helping SaaS Leader Process 13M Texts Daily for AI Training

Learn how a leading SaaS company achieved 90% cost reduction in data masking while protecting sensitive PII/PHI across 13M daily texts to power their AI innovation.
Read the case study
Book a demo

See Protecto on your own data

Book a demo to see how Protecto finds and masks sensitive data before it reaches any AI model.

Book a demo
Talk to sales
New: run any AI model without exposing real values.
See how it works