Runtime security for AI systems. Detection and Response for prompts, outputs, and AI agents.

🌐 vigilguard.ai · ✉️ contact@vigilguard.ai

Vigil Guard delivers a runtime security layer for the AI stack, from LLM applications to autonomous AI agents. Founded in 2026 by Tomasz Bartel, a security practitioner with 20+ years in cybersecurity (CrowdStrike, Cisco, IBM, Riverbed). We give enterprises the same visibility and control over AI and agentic systems that they already have over networks, endpoints, and identities.

AI moved into the enterprise faster than the controls built to govern it, and AI agents are widening that gap. Traditional security tools cannot see what a model is being asked, what it returns, which tools an agent calls, or how it behaves across a long-running session. Guardrails and policies are not operational security. Shadow AI spreads across browsers and SaaS, agentic systems take real actions on production data, and natural language becomes instruction, data, and attack vector at the same time.

Vigil Guard treats natural language, and every agent interaction (prompts, tool calls, outputs, multi-turn drift), as a new control plane. The platform detects prompt injection, jailbreaks, data exfiltration, token smuggling, Unicode exploits, and scope drift across agent sessions, and enforces ALLOW / SANITIZE / BLOCK controls on models and agents in real time.

• Scope drift detection for agentic systems
• PII protection with automatic language detection
• Content moderation
• Custom rule authoring for organization-specific policies
• Self-learning FP/FN feedback loop that tunes detection to your environment over time

100% on-prem, Docker-based, air-gapped, cosign-verified, with zero external dependencies. Integrates with existing SIEM, Python SDK, n8n, and LiteLLM.

Think EDR, but for prompts, outputs, and agents.

• Website: vigilguard.ai
• General inquiries: contact@vigilguard.ai

For product details, pricing, deployment options, and trial access, visit vigilguard.ai.