u/Zealousideal_Pace127

Hey folks 👋

Solo dev from Ludhiana, India. Just shipped my first SaaS and would love feedback before I push it harder.

What it is: ListingClimb scans Amazon India listings and scores them on three dimensions:

• Keyword coverage (do you cover what buyers actually search)
• Rufus optimisation (will Amazon's new AI surface you for conversational queries)
• Conversion clarity (bullets, A+ readiness, title structure)

Free scan, no signup needed. Optional AI-powered rewrites for ₹149/scan (~$1.80). No subscription.

Why I built it: Every existing tool (Helium 10, ZonGuru, etc) is a US-priced subscription. Indian sellers don't subscribe to SaaS the same way US ones do, and they want pay-per-use. Plus, none of them leads with Rufus, which is genuinely changing how listings get found on Amazon now.

Stack

• Supabase (auth + DB + RLS)
• Anthropic API (Claude Haiku for analysis, Sonnet for rewrites)
• Razorpay for INR payments
• Apify for Amazon data scraping (CAPTCHA was a nightmare — solved with a "paste listing" mode as primary UX)
• Vercel + Upstash Redis for rate limiting

The hard parts

1. Amazon CAPTCHA blocking server IPs → moved to "paste listing text" as primary flow
2. Free scan abuse prevention → device fingerprint + IP record + per-account flag
3. Razorpay verification edge cases → HMAC + server re-fetch + timing-safe compare

What I'd love feedback on

1. The Rufus angle — leading with it, or burying it?
2. Anything obviously broken when you scan a listing

Site: listingclimb.com

Roast away. Honest critique > polite encouragement