fiund vs Opendatabay

The core differences

Both are licensing-first marketplaces; the trust model differs. Opendatabay verifies sellers at the storefront level with provider-written licences per listing; fiund attaches the signed licence and consent records to the file itself.

Opendatabay’s catalog is listing-dependent and weighted toward open and synthetic data available elsewhere; fiund lists non-public, owner-licensed audio and video that is not already in the crawl.

Pricing shape: Opendatabay is self-serve, with seller-set prices and a published 5–30% tiered commission; fiund is brief-driven rather than browse-and-buy.

Where Opendatabay wins

A young UK marketplace for buying and selling AI-ready datasets — breadth and self-serve convenience, with a licensing-first pitch still being proven.

• Self-serve breadth - open, synthetic, and premium datasets across many modalities in one storefront, with instant access
• Published fee schedule - a rare bit of pricing transparency; the tiered 5–30% seller commission is public
• Licensing-first framing - seller verification and rights-cleared positioning, uncommon for a general data marketplace

Useful for teams that want to browse off-the-shelf, synthetic, or open datasets without a sales cycle; per-listing rights depth is the thing to check before relying on it for media training data.

Where fiund wins

• Provenance you can defend. Every asset carries a signed licence with explicit AI-training rights and separate voice/likeness consent.
• Not already in the crawl. Non-public material sourced from owners, so you aren't paying for what your model has already seen.
• Sourced to brief. If the dataset doesn't exist yet, fiund goes and sources it.

How to choose

Pick on the axis you actually care about. If defensible chain of title and documented consent are the gate, fiund is built for that. If your need matches Opendatabay's core model — licensed marketplace — the full Opendatabay review is honest about where it leads.