AI Model Guardrails

Votal AI Model Guardrails is a runtime enforcement platform that sits inline between users, applications, and AI models to monitor, inspect, and control AI interactions in real time. The platform operates as a control plane that intercepts every prompt and response, applying policy-driven rules to detect and mitigate threats such as prompt injection, jailbreaks, and sensitive data leakage before they reach end users or external systems. Core functions include: - Inline inspection of prompts and model responses - Blocking, redacting, or transforming unsafe inputs and outputs - Detection and redaction of PII, secrets, and proprietary data - Policy authoring with enforcement actions (block, redact, transform) - Context-aware and role-based access controls - Continuous monitoring with drift detection and policy violation alerts - Audit-ready logs and dashboards for compliance reporting The platform supports a phased deployment model: shadow mode for baseline observation, followed by active enforcement. It is designed to be vendor-agnostic, supporting multiple LLM providers and AI model types including RAG pipelines and AI agents. Deployment options include VPC, on-premises, and private cloud environments. Compliance alignment is noted for SOC 2, ISO 27001, and the EU AI Act. Reported performance metrics from enterprise deployments include a 99.4% live attack block rate, under 0.8% false positive rate, and inline latency of approximately 60-95ms per request. Target use cases include enterprise AI copilots, customer support chatbots, hiring workflow automation, internal AI tools, and RAG pipelines.