AI Data Firewall
Unlock AI across customer support, operations, and financial workflows without exposing payment data, PII, or other sensitive fields to models.
The VGS AI Data Firewall sits between your application and AI systems to automatically detect and tokenize sensitive data, enforces policies, and safely reconstruct responses.
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AI Adoption is Blocked by Sensitive Data
Security teams block deployment because of the risk of customer data exposure to AI models. Teams end up building fragile redaction systems internally, slowing AI adoption. VGS prevents this by:
Protecting sensitive data
VGS will protect and tokenize payment cards, SSNs, bank accounts, addresses, health data, and more before inference.
Centralizing AI policy control
VGS is able to mask, tokenize, or block fields based on environment, endpoint, and workflow all in one place.
Shipping AI faster
VGS helps to remove security bottlenecks and avoid maintaining brittle, duplicated redaction code.
The Solution: VGS AI Data Firewall
Designed as the trusted agentic infrastructure that speeds up AI adoption.
Shipping AI faster
A proxy layer between your applications and AI models.
Automatic detection
Identify sensitive fields in structured and unstructured payloads.
Tokenize, mask, or block
Apply policies consistently across every AI workflow.
Safe reconstruction
Reconstruct responses for authorized downstream systems.
How VGS AI Data Firewall Works
VGS intercepts requests and responses so your AI stack only sees protected data.
Your app sends an AI request
Prompts, tickets, transcripts, or transaction context flow toward an AI provider or internal model.
VGS intercepts the payload
Route traffic through VGS in the data path-no scattered redaction logic across microservices.
Sensitive fields are protected
Automatically tokenize, mask, redact, or block based on your policy (e.g., PAN always tokenized; PII masked in non-prod).
The AI model processes safe data
The model receives only non-sensitive tokens and context, enabling useful inference without exposure.
Responses return via VGS for safe reconstruction
Reconstruct allowed values for authorized systems and log events for audit and compliance automation.
Common AI Use Cases
Protect sensitive data while still enabling high-utility AI features across teams.
AI customer support
Summarize tickets and coach agents while tokenizing payment data and masking PII inside prompts and transcripts.
Financial AI Workflows
Analyze reconciliation and dispute flows while keeping PANs, bank accounts, and identifiers protected.
Ops Automation
Use AI on logs, runbooks, and incident context without exposing secrets and sensitive customer attributes.
Built for Regulated Industries
Unlock AI adoption where compliance and privacy are non-negotiable.
Fintech
Tokenize payments and identify data for AI-enabled customer experiences.
Insurance
Protect policyholder PII while enabling AI workflows for claims and support.
Healthcare
Shield sensitive records when using AI assistants and automation tools.
Why Teams Use VGS for AI Security
A security layer every AI application can rely on-built on provel tokenization infrastructure.
Reduce scopt & offload risk
Keep raw sensitive data out of AI pipelines to reduce exposure and simplify compliance posture.
Enforce consistent policies
One place to define what data is allowed into which AI tools, environments, and enpoints.
Move faster in regulated orgs
Remove the need for fragile DIY redaction systems to unblock AI rollouts.
Ready to Get Started?
Talk to a VGS expert to map your AI workflows and define protection and reconstruction policies.
FAQs
A security layer that sits between applications and AI models to control what data flows into and out of AI systems, applying detection and protection policies before inference.
The AI Data Firewall is designed as an infrastructure layer—route requests to third-party AI providers or internal models while keeping sensitive fields protected.
DIY redaction is often duplicated across services and hard to keep correct over time. VGS centralizes detection and policy enforcement in the data path.
VGS protects sensitive data including Payment cards, bank accounts, SSNs, addresses, health data, and other sensitive identifiers—depending on your configured detection and policy rules.
Yes, policies can block requests, allow only tokenized payloads, or restrict specific fields by environment and endpoint.
Start with a discovery call to map AI workflows, identify sensitive data touchpoints, and define policies for protection and reconstruction.