Maybe Don't AI offers an enterprise security layer for AI agents, intercepting and analyzing outbound requests before execution. The platform uses AI-specific policies, traditional engines, and anomaly detection to block harmful actions and ensure compliance. This provides real-time auditing and visibility into agent activity for enhanced security.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents, operating autonomously, frequently execute actions that result in significant financial losses or security vulnerabilities due to their inability to adhere to predefined operational constraints. The lack of real-time oversight for these agent-initiated requests creates substantial risk for enterprises.
Solution
Maybe Don't AI provides an enterprise-grade security layer for AI agents by intercepting and analyzing their outbound requests prior to execution. The platform employs a multi-layered approach, integrating AI-specific policy enforcement, traditional policy engines, and anomaly detection algorithms to preemptively identify and block potentially harmful actions. This ensures that AI workflows operate within defined security perimeters and compliance frameworks. Real-time auditing capabilities offer continuous visibility into agent activity, enabling rapid response to emergent threats and providing a robust audit trail for compliance purposes. The system is designed for straightforward integration, allowing organizations to enhance their AI security posture with minimal deployment overhead.
Target Audience
The primary customers are enterprises deploying AI agents for operational tasks, particularly those in regulated industries or handling sensitive data, who require robust security and compliance controls.
Features
- Request interception and analysis engine for AI agent outbound communications.
- Multi-modal policy enforcement combining AI-native policies, traditional rule-based engines, and behavioral anomaly detection.
- Real-time auditing and logging of all AI agent requests and system responses.
- Plug-and-play API for rapid integration into existing enterprise infrastructure.
- Human-in-the-loop (HITL) workflow support for manual validation of high-risk operations.
- Anomaly detection models trained to identify deviations from expected agent behavior.
- Centralized dashboard for monitoring AI agent activity and managing security policies.