In FY26, I led the design and successful security approval of Agent Feedback Engine, a production-ready internal AI solution that transforms raw customer call transcripts into structured feedback and actionable trend data. This two-part series details the initiative from its secure architectural foundations to its operational impact on the business.
Deep Dive into Key Initiatives
The following sections provide detailed breakdowns of the strategic pillars that contributed to this transformation. Each deep dive explores the specific problems I identified, the objectives I set, and the solutions I designed and implemented.
Part 1: Secure AI Foundations
A deep dive into the foundational architecture of Agent Feedback Engine, focusing on secure data handling, trust, and safety.
View Part 1 →Part 2: Operationalizing the System
An analysis of the operational workflow, strategic recommendations, and business impact of the Agent Feedback Engine system.
View Part 2 →Executive Summary
In this two-part series, I detail how I led the design, security approval, and operational rollout of Agent Feedback Engine, an internal AI solution that converts raw customer call transcripts into structured feedback. Part one focuses on the foundational work required to pass Microsoft's rigorous security and privacy reviews. I outline how I designed a defensible and extensible architecture, navigated internal policy ambiguity, and engineered specific mitigations for platform limitations and AI hallucinations to build a system that was trustworthy and auditable.
Part two shifts to operationalizing the system. I detail the workflow I designed to standardize how insights are captured and formatted, eliminating manual re-work for frontline managers. This section also covers the trend analysis agent I built to aggregate individual reports into actionable, executive-level recommendations, and the change management strategy I led to embed the AI into existing business operations and quality frameworks. Together, these articles document the end-to-end process of turning a complex business need into a secure, practical, and impactful AI-driven system. The initiative is now referenced in our quarterly business reviews up to the FastTrack executive director as a model for secure, high-trust AI adoption.