Case Study
Feedback Analyzer
An AI automation workflow built to process large feedback streams with minimal manual effort. The platform ingests spreadsheet feedback, enriches it with OpenAI sentiment and intent analysis, and posts actionable summaries directly to Slack channels.
Python
OpenAI API
AWS Lambda
error_outline The Problem
Manual feedback triage was slow and inconsistent. Teams were spending hours reading comments, grouping themes, and posting updates manually, which delayed product decisions and customer response loops. A reliable, automated classification and notification pipeline was required to keep operations real time.
account_tree Automation Architecture
table_view
Google Sheets
rate_review
Feedback Forms
forum
Support Queue
hub
Analysis Orchestrator
Lambda + OpenAI
psychology
OpenAI Analysis
notifications_active
Slack Alerts
terminal Tech Stack
Language
Python
AI Engine
OpenAI API
Orchestration
AWS Lambda
Input
Google Sheets API
Delivery
Slack API
analytics Impact
speed
-85%
Manual Processing Effort
schedule
Near Real-Time
Team Notifications
insights
Consistent
Sentiment and Intent Classification