QIAIP

Peyman M. Hassan’s independent applied research project studying multi-agent orchestration, RAG, governed tool calling, evaluation agents, and human-in-the-loop decisions in enterprise AI architecture.

How can agents retrieve organizational knowledge, coordinate specialized roles, use governed tools, and collaborate with human decision-makers?

Conceptual research architecture. This diagram describes the study direction; it is not a deployment or performance claim.

Assets, maintenance, work orders, leases, vendors, and property operations serve as research scenarios and test domains for structured, traceable AI workflows. These scenarios support technical study and are not commercial product offerings.

The study examines evaluation agents, permissions, auditability, and human review. Evaluation priorities include task completion, routing accuracy, groundedness, tool-call correctness, permission compliance, approval escalation, latency, and recovery from tool failures. Published benchmark results are not yet included in this portfolio.

An independent research and engineering project by Peyman M. Hassan, presented through Avehar.

Personal research and independent projects presented through Avehar do not use proprietary employer source code, confidential documentation, customer data, credentials, or trade secrets belonging to an employer or third party.