Why you need an AI security gateway
Organisations deploying LLMs and AI agents face critical security risks that traditional tools can't address
Prompt Injection Attacks
Malicious inputs manipulate model behavior, bypassing safety controls
Sensitive Data Exposure
PII, credentials, and proprietary information leak through prompts and responses
Compliance Gaps
No audit trail for AI interactions means failed regulatory requirements
Uncontrolled Access
Lack of policy enforcement between applications and AI providers
Introducing RAGuard
A Security Gateway for the AI Era
RAGuard sits between your applications and LLM providers, inspecting every request and response in real-time. It detects threats, enforces tenant-specific policies, redacts sensitive data, and maintains a complete audit trail all without requiring changes to your AI models or provider contracts.
Deploy as a proxy endpoint
Integrate in minutes
Protect immediately
Core Capabilities of RAGuard
Comprehensive Protection Across the AI Lifecycle
Threat Detection
Block prompt injection, jailbreak attempts, and adversarial inputs before they reach your models
Data Protection
Automatically detect and redact PII, credentials, and sensitive information in prompts and responses
Policy Enforcement
Define tenant-specific rules with policy-as-code using Open Policy Agent (OPA)
Audit & Compliance
Capture every interaction with immutable logs, risk scores, and ZKP-based evidence bundles for tamper-proof attestations
05
OPA Policy Framework
Define granular, tenant-specific rules in Rego. Control detection thresholds, enable/disable features, set redaction rules, and manage rate limits all version-controlled and instantly deployable.
06
Multi-Model Support
Native adapters for OpenAI and Anthropic APIs. Standardized interface handles request/response transformation, streaming support, and provider-specific authentication.
07
ZKP-based Evidence Engine
Generate tamper-proof audit trails using Zero-Knowledge Proofs. Prove compliance without exposing content, with SHA-256 hashing and signed manifests for independently verifiable evidence.
02
Content Safety Classification
Identifies harmful content across five categories: hate speech, insults, sexual content, violence, and misconduct. Configure per-category actions block, mask, or log based on your risk tolerance.
03
Data Loss Prevention (DLP)
Detects and redacts structured data (emails, phone numbers, SSNs, credit cards) and unstructured entities (names, organizations, locations) using pattern matching and Named Entity Recognition. Includes secret scanning for API keys and credentials.
04
Response Filtering
Post-processing layer that sanitizes LLM outputs before returning to users. Catches credential leakage in generated code, hallucinated PII, and policy violations in model responses.
01
Prompt Injection Detection
Two-tier detection combining fast regex patterns with ML-based classification (Meta Prompt Guard 2). Catches known attack patterns, encoded payloads, and novel injection attempts with configurable confidence thresholds.
Security Features Built for Production AI
Protect your AI in production with multi-layer defense: prompt security, content moderation, DLP, policy governance, and cryptographically verifiable audits