EchoFeederAI

Problem & Motivation Organizations struggle with fragmented and emotionally heavy feedback: HR escalations, product issues, engineering blockers, legal concerns, customer pain points, and team-to-team friction. Traditional systems like surveys, JIRA tickets, or ad-hoc email threads fail to capture emotional tone, urgency, or clarity. EchoFeederAI addresses this gap by providing a unified, intelligent channel that converts raw feedback—often chaotic, emotional, and unstructured—into actionable, role-specific insights. Solution & How It Works EchoFeederAI uses an agentic pipeline built on IBM watsonx Orchestrate to process feedback end-to-end. A user submits a set of concerns, and the system routes the feedback through a multi-stage workflow: intake → NLU-based analysis → role-aware synthesis → recommended best practices → optional scheduling suggestion. Each stage is handled by a dedicated agent or a single orchestrated flow, ensuring that feedback is correctly interpreted and transformed into structured outputs. Outcome & Impact The system produces empathetic user summaries, professional recipient summaries, and practical best-practice recommendations tailored to roles like HR, Legal, Product, Engineering, Management, or Customer Success. This not only accelerates problem-resolution and reduces iscommunication but also ensures transparency, emotional safety, and traceability. EchoFeederAI can serve as a standalone feedback-resolution tool or integrate with larger organizational workflows, making it a versatile building block for modern, human-centered operations.