Corbenic Launches Secure AI Memory Tool
Corbenic AI launched a beta tool for encrypting and auditing stored AI working memory.
AI memory is becoming a new security surface. As assistants and agents retain more context across sessions, companies need ways to protect what those systems remember.
What happened
Corbenic AI launched the beta of Galahad, a tool designed to encrypt stored AI working memory, separate customer data and record AI activity for later investigation.
The tool supports existing AI software including vLLM, SGLang and llama.cpp, positioning itself as an infrastructure layer for teams running or deploying AI systems.
Why it matters
Enterprise AI adoption creates new questions around what data is stored, how long it remains accessible and whether activity can be audited after something goes wrong.
Secure memory tools could become part of the broader AI governance and security stack, especially for agentic systems that need persistent context.
The bigger picture
The more AI systems act like long-running coworkers, the more memory becomes both a feature and a risk. Startups that make memory encrypted, isolated and reviewable may become important to enterprise trust.