I built an AI tool that analyzes your Discogs vinyl collection

I built recordsv.lt to explore a problem I ran into as a vinyl collector: once your collection grows, Discogs is great for cataloging but not great for understanding the collection itself.

Recordsv connects to Discogs and analyzes your collection using the full release metadata — not just album titles but pressings, contributors, labels, and release history. The idea is to surface patterns that are hard to see manually.

Some examples: * Pressing insights – compares different pressings of the same album and highlights when the version you own might not be the best sounding or most collectible one. * Contributor networks – maps relationships between artists, producers, engineers, and labels across your collection. You often discover unexpected connections between records. * Collection analytics – shows patterns in decades, genres, labels, and recording locations across the collection. * Contextual reviews – aggregates reviews and commentary about specific releases rather than just the album.

Tech stack: - Next.js - Discogs API - vector search for similarity across releases - AI summarization for reviews and metadata

It’s optimized for large collections (tested with ~2000 records so far).

Curious what other collectors or Discogs users think. Would also love feedback on what kinds of analysis would actually be useful.

Best, tom