# AI Product Feedback Assistant — Insight Pipeline Demo

## Purpose
Portfolio demo for product support, product operations, AI implementation, and workflow automation roles.

## Problem
Product teams receive feedback from app reviews, support tickets, emails, interviews, and social comments. Valuable themes get buried because feedback is scattered and manually reviewed.

## Solution
A lightweight AI-assisted feedback pipeline that classifies raw feedback, extracts themes, suggests product opportunities, and turns repeated issues into prioritized actions.

## Workflow
1. Import raw feedback from support tickets, reviews, or survey responses.
2. AI tags each item by theme, sentiment, severity, and user intent.
3. Assistant clusters repeated issues into product themes.
4. System generates:
   - support response draft
   - product insight
   - suggested backlog item
   - confidence / review flag
5. Dashboard surfaces top themes and next actions.

## Tools represented
- Feedback collection
- AI classification and clustering
- Support response drafting
- Product insight generation
- Prioritized backlog handoff

## What this demonstrates
- Product operations thinking
- Customer/user translation
- AI-assisted analysis
- Support-to-product workflow design
- Practical automation that keeps a human in the loop

## Resume framing
Created a portfolio prototype of an AI product feedback assistant that classifies user feedback, clusters recurring themes, drafts support responses, and converts repeated issues into prioritized product opportunities.

## Next production version
Could be built with Intercom/Zendesk/Freshdesk exports + Airtable/Notion + OpenAI/Claude + Linear/Trello/Jira.