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LensMatch: Lens Classification API + Embedded Widget

A lightweight JavaScript widget that camera retailers, rental shops, and used-gear marketplaces embed on their product pages. User inputs focal length (or selects from a dropdown), and the widget instantly displays the lens category, typical use cases, and a visual comparison to similar lenses. The widget pulls from a free, open-source lens database (built and maintained by the creator) and offers a paid API tier for high-volume queries. Works offline after first load.

PLUGIN

15 weeks • 70% confidence

Value Proposition

Sellers and platforms reduce buyer confusion and returns by instantly showing lens category. Buyers make faster, more confident purchasing decisions. Creators own the data layer (lens database) and can monetize both the free widget (affiliate links to retailers) and the API (for high-volume integrations).

Target Audience

Used-gear marketplaces (eBay, Reverb, local Facebook groups), camera rental shops, photography education platforms, camera store websites, lens review blogs

Key Features

  • Embed-ready JavaScript widget (single line of code to install)
  • Focal-length input → instant category output (wide-angle, macro, standard, telephoto, etc.)
  • Visual comparison: shows this lens against 3–5 similar lenses in the same category
  • And more, with full implementation detail...

Tech Stack

Vanilla JavaScript (no frameworks) for widget Node.js + Express or Python Flask for API backend PostgreSQL or MongoDB for API usage tracking GitHub for open-source lens database
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Original Problem

Photographers struggle to quickly classify lenses without memorizing technical specifications

Photography enthusiasts and professionals frequently need to determine lens categories (wide-angle, macro, standard, telephoto) but lack a simple mathematical framework to do so. They either memorize focal length ranges or rely on manufacturer labels, which creates friction when evaluating used equipment, comparing lenses across brands, or teaching others. Current solutions require domain knowledge or manual lookup rather than a universal formula.

Score: 17.5%