Close the AI risk gap your stack cannot see.
Get AI-specific visibility, prompt-aware controls, and an audit trail for actions your existing tools were never built to inspect.
Enterprise AI security covers the controls, policy enforcement, and audit mechanisms needed to reduce data leakage, unauthorized agent actions, and compliance exposure introduced by AI systems.
Four security gaps Qadar closes from day one.
Enterprise AI security capabilities
Full AI activity visibility
Every AI tool in use across the company — not just the ones IT approved. Real-time view of which teams are calling which models with what data volume.
Structured audit log
User identity, model, data category, policy outcome, timestamp — all queryable. SIEM export via webhook or S3 for your security operations team.
Agent kill switch
Pause or block any autonomous AI workflow instantly from the Qadar control plane. No engineering ticket, no service interruption to other agents or workflows.
Cyber insurance documentation
AI governance policy documentation and audit trail ready for insurer review. SOC 2 Type II controls documentation available on Enterprise tier.
GDPR and EU AI Act readiness
Redacted-body logging keeps you GDPR-compliant. EU data residency option (Enterprise) for cross-border data restrictions. DPO-defensible audit records from day one.
MCP governance (Enterprise)
Policy enforcement for Model Context Protocol tool calls — the emerging standard for AI agent tool access. Qadar extends governance to MCP-based agent architectures.
What CISOs ask in the first briefing
What are the main AI security risks a CISO needs to address today?
The three highest-priority risks are: (1) data exfiltration through AI prompts — employees sending client data, PII, or proprietary content to AI models without controls; (2) uncontrolled AI agent actions — autonomous agents accessing systems, calling APIs, or taking actions without human review or audit; and (3) compliance exposure — the inability to demonstrate to auditors, regulators, or cyber insurers that AI use across the organization is governed and logged.
Does Qadar replace our existing DLP or SIEM?
No — Qadar operates at the AI layer and is designed to feed your existing security stack. Audit logs can be exported to your SIEM via webhook or S3. Qadar covers what DLP cannot: the semantic content of AI prompts and the behavioral trace of AI agent actions. It is additive, not a replacement.
How do you audit AI agent behavior across an organization?
Through a centralized control plane that intercepts every agent action — tool calls, API requests, data reads — and logs the full trace: what the agent was instructed to do, what tools it called, what it received back, and what policy decision was applied. Qadar provides this as a structured audit trail, queryable and exportable to SIEM.
What is the fastest way to get AI activity visibility today?
Route your organization's AI traffic through the Qadar gateway. The deployment requires one configuration change per application or team. From the first request, every AI call is logged with the structured schema your security team needs. No new infrastructure, no retroactive data collection.