OrchestrAI: A Proactive Delegated Communication System with Stateful Agent Orchestration, Risk-Aware Action Gating, and Human-in-the-Loop Governance

Modern knowledge workers face persistent challenges in managing multi-channel coordination tasks spanning emails, calendar events, and follow-up communication. Existing digital assistants are either reactive command-driven tools or rigid rule-based automation systems that lack contextual reasoning and workflow continuity needed to act autonomously on behalf of a user. This paper presents OrchestrAI, a stateful delegated communication system that combines LangGraph-based multi-step agent orchestration with a risk-aware policy engine and a human-in-the-loop approval interface. The system autonomously scans Gmail inboxes, classifies threads, extracts structured tasks and commitments, detects SLA breaches, and drafts follow-up nudges enriched with Google Calendar context. Every proposed outbound action is scored for risk, gated behind an explicit approval workflow, and recorded in an immutable audit trail. Evaluation across ten delegated-communication scenarios shows that OrchestrAI achieves a safety catch rate of 100%, compared to 40% for a one-shot LLM baseline and 0% for a rule-based system, while maintaining comparable task success rates. These results demonstrate that stateful orchestration combined with governance-aware action gating provides a measurably safer foundation for inbox-automation agents than single-turn or rule-driven approaches.