Enterprise AI Security Deploy AI Without Deploying Risk
Security controls, architectures, and governance frameworks for deploying AI without data leakage, model manipulation, or compliance violations. We build AI systems AND secure them, eliminating the gap between AI teams and security teams.
How We Secure AI Systems
Security decisions made at the architecture stage, before a single model is deployed.
Data & Model Protection
- Data leakage prevention with DLP policies, API gateway rules, and content inspection
- Prompt injection defense: input validation, boundary enforcement, output filtering
- Model integrity monitoring with cryptographic signing and drift detection
- Automated PII/PHI detection at the input layer for private AI deployments
Governance & Compliance
Secured AI vs. Unsecured AI
Encrypted, Segmented, Controlled
TLS 1.3 in transit, AES-256 at rest, customer-managed keys, network segmentation, and DLP inspection on every AI data path.
RBAC with MFA and Full Audit
Role-based access integrated with your IdP. Privileged actions require MFA and approval workflows. Every access event logged for audit.
Defense-in-Depth Protection
Input sanitization, boundary enforcement, output filtering, and behavioral monitoring at every interaction point between users and models.
Continuous Monitoring
Cryptographic model signing, behavioral baselines, and automated drift detection alerts before compromised outputs reach production.
Why Choose PTG for AI Security
We Build AI AND Secure It
Most organizations hire one vendor to build AI and another to audit it. We are both teams in one. Security decisions are made at the design phase, not discovered at the assessment phase.
24 Years of Security First
We were a cybersecurity firm for two decades before adding AI services. Our security expertise is the foundation our AI practice was built on.
Credentials Auditors Recognize
Craig Petronella is a CMMC Registered Practitioner, Licensed Digital Forensic Examiner, and author of 15 cybersecurity books.
Zero-Breach Track Record
2,500+ clients across 24 years with zero breaches. BBB A+ rating maintained continuously since 2003. That record extends to every AI deployment.
Frequently Asked Questions
What are the biggest security risks of enterprise AI?
Data leakage to external AI services, prompt injection attacks, model poisoning through corrupted training data, unauthorized API access, and shadow AI usage by employees. Each requires specific technical controls that most organizations lack.
Can AI deployments meet CMMC Level 2 requirements?
Yes, with proper architecture. CMMC Level 2 requires 110 security practices across 14 domains. We deploy AI in environments meeting all applicable requirements with documentation your C3PAO assessor needs. Craig Petronella is a CMMC Registered Practitioner.
How do we secure AI tools employees are already using?
Start with an AI inventory and risk assessment. Then implement a three-track approach: secure approved tools, block high-risk unauthorized tools, and deploy approved alternatives. We establish AI acceptable use policies and conduct security training.
What does an AI security assessment cost?
AI security assessments typically range from $10,000 to $30,000 depending on the number of AI systems, data sensitivity, and compliance requirements. Includes tool inventory, risk evaluation, remediation recommendations, and compliance gap analysis.
How do you protect against prompt injection attacks?
Defense-in-depth: input sanitization stripping known injection patterns, prompt boundary enforcement separating system instructions from user input, output filtering blocking sensitive content, and behavioral monitoring flagging anomalous interactions.
Secure Your AI Before It Becomes a Vulnerability
Get an AI security assessment from the team with 24 years of cybersecurity expertise and zero breaches.