The pattern is always the same. A customer submits a feature request, another submits the same one two weeks later, and by the end of the quarter the same request is sitting across multiple tickets from different accounts.
Someone has to manually go through every ticket, identify the pattern, and write up individual feature requests engineering can access and prioritise.
This tool changes that. Submit a request, filter the queue, run the analysis, and export a PDF document you can hand straight to engineering.
Built because when the process lives in a system, nothing falls through the gaps.
Live demo · Case study · Source
Mock tickets are already loaded. Submit your own or use the existing ones, then open the dashboard to run the analysis and export a brief.
Step 1 — Submit and filter
Log feature requests by request type (Authentication, API, Integrations, User Management, Billing) and account tier (Enterprise, Pro, Free). Filter the queue by type and account, then select the tickets you want to analyse.
Step 2 — Analyse
Claude groups the selected tickets into themes, scores each by priority based on how frequently it appears and which account tiers are asking for it, and returns a summary with recommended actions and affected accounts.
Step 3 — Export
Download a PDF document with the full brief and supporting evidence for each ticket. The document includes a theme summary, the accounts affected, a recommended action for engineering, and a breakdown of each ticket with the feature request and why it matters to the customer.
When ten free users and one enterprise account ask for the same thing, they are not equal requests. The enterprise account has a contract, a renewal conversation, and a support engineer whose time depends on the resolution.
Feedback Loop scores priority using both frequency and account tier so the output reflects how a product team would actually prioritise, not just how many customers asked.
Cursor · JavaScript · Anthropic Claude API · Cloudflare Workers · Workers KV · jsPDF · Cloudflare Pages
git clone https://github.com/KhanKMadiha/feedback-loop.git
cd feedback-loop
npm startOpen:
To run AI analysis locally, start the Worker proxy in a second terminal:
npm run dev:proxyCopy workers/.dev.vars.example to workers/.dev.vars and add your Anthropic key:
ANTHROPIC_API_KEY=sk-ant-api03-your-key-here
Restart npm run dev:proxy after editing .dev.vars.
feedback-loop/
data/mock-tickets.json # Sample tickets by request type
src/ # Dashboard, intake form, settings
workers/proxy.js # Cloudflare Worker — API proxy and rate limiting
Support Ticket Analyser: khankmadiha.github.io/support-ticket-analyser
Articulate: articulate-app-production.up.railway.app
Portfolio: madihaintech.me
MIT — use and adapt freely, attribution appreciated.