Memoryful Guardrail offers intention‑time detection for AI agents by compressing each prompt stream into a bounded “memory of intent.” This persistent intent memory lets the system identify cross‑session or multi‑step attacks before the model executes harmful actions, complementing traditional SIEM and UEBA tools that only react after activity occurs. The solution monitors tool calls, file writes, logs, and network flows to provide continuous threat visibility across agents and sessions.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents can execute malicious actions across multiple sessions, allowing attackers to split an attack into small steps that evade detection by traditional, session‑bound security tools. Existing SIEM and UEBA solutions only monitor events after the agent has acted, leaving a gap for cross‑session and intent‑based threats.
Solution
Memoryful Guardrail addresses this gap by compressing each prompt stream into a bounded “memory of intent” that persists across sessions and agents. The platform continuously monitors computational, tool‑call, file‑write, log, and network events, linking them to the intent memory to detect malicious behavior before the agent executes harmful actions. By integrating with existing SIEM and UEBA infrastructures, it surfaces threats that would otherwise remain hidden between messages. The solution provides both event‑level analytics and higher‑level intent detection, enabling security teams to intervene early and protect AI‑driven systems.
Target Audience
Primary customers are enterprises and organizations deploying autonomous AI agents or LLM‑powered applications that require advanced security monitoring, as well as security operations teams using SIEM/UEBA solutions.
Features
- Bounded intent memory that aggregates and compresses prompt streams for cross‑session threat visibility
- Real‑time monitoring of computational, tool‑call, file‑write, log, and network events linked to intent state
- Persistence of intent memory across multiple agents and sessions to catch distributed attacks
- Seamless integration with existing SIEM and UEBA platforms for unified security reporting
- Event‑surface analytics that surface threats before the AI agent takes action
- Support for agent behavior analytics, including residual‑stream and belief‑state monitoring