AgentVault Architecture
Middleware layer between AI agents and external systems. Security, control, and visibility at runtime.
Overview
AgentVault is positioned as a middleware layer between AI agents and external systems. It enforces security, control, and visibility at runtime.
AgentVault separates agent logic, credential storage, and system execution.
AI Agent
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Execution Environment
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AgentVault
├── Vault (credentials)
├── Profiles (permissions)
├── Sessions (runtime control)
└── Audit Trail (logs)
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External Systems (APIs, DBs, Services)
This separation is critical for security.
Core Components
Vault
Stores credentials securely. Properties: encrypted, isolated, not directly accessible.
Profiles
Define rules for access. Profiles control allowed actions, restricted actions, and data filtering.
Session Manager
Controls runtime behavior: start and stop execution, limit session duration, revoke access instantly.
Audit Trail
Tracks all activity including requests, decisions, and execution logs.
Data Flow
Step-by-step execution:
Trust Boundaries
AgentVault enforces strict boundaries:
- Agents cannot access credentials directly
- External systems cannot be accessed without validation
- All interactions are controlled
Security Flow
- Start with no permissions
- Grant minimal required access
- Monitor all actions
- Revoke access when needed
Deployment Models
Local Deployment
Runs on user machine. Maximum control and privacy.
Backend Deployment
Integrated into application server. Centralized management.
Middleware Layer
Sits between agent and APIs. Lightweight and flexible.
Scalability
AgentVault is designed to scale across multiple agents, multiple profiles, and multiple sessions. Each agent can operate independently with its own rules.