This issue introduces the implementation plan for an agentic AI workflow architecture within our AI GRC platform. The goal is to evolve the current AI advisor into a more autonomous, modular, and secure system capable of executing structured workflows, coordinating multiple agents, and safely performing write operations with human oversight.
The first phase will focus on enabling AI write tools with a human-in-the-loop approval layer. This includes implementing tool-level approval flows, rule-based auto-approval logic, and security guardrails to prevent unsafe operations. A state-machine driven approval gateway will manage transitions such as pending → approved → executed while maintaining auditability and integration with existing approval workflow tables.
In later phases, the system will expand into a multi-agent architecture where specialized agents (e.g., risk, compliance, vendor agents) collaborate through an orchestration layer. Additional capabilities such as proactive workflows, anomaly detection, and persistent AI memory will gradually be introduced to enable autonomous compliance monitoring and intelligent governance recommendations across the platform.
This issue introduces the implementation plan for an agentic AI workflow architecture within our AI GRC platform. The goal is to evolve the current AI advisor into a more autonomous, modular, and secure system capable of executing structured workflows, coordinating multiple agents, and safely performing write operations with human oversight.
The first phase will focus on enabling AI write tools with a human-in-the-loop approval layer. This includes implementing tool-level approval flows, rule-based auto-approval logic, and security guardrails to prevent unsafe operations. A state-machine driven approval gateway will manage transitions such as pending → approved → executed while maintaining auditability and integration with existing approval workflow tables.
In later phases, the system will expand into a multi-agent architecture where specialized agents (e.g., risk, compliance, vendor agents) collaborate through an orchestration layer. Additional capabilities such as proactive workflows, anomaly detection, and persistent AI memory will gradually be introduced to enable autonomous compliance monitoring and intelligent governance recommendations across the platform.