The experimental project, called CoinSharesNFTAI, aggregates different sets of data to provide a user with what it determines is a fair price for a rotating list of top NFT collections on OpenSea

Europe-based digital asset management platform CoinShares released an experimental artificial intelligence (AI) bot on Thursday that might be able to help traders determine a fair price for some non-fungible tokens (NFT).

The experimental project, called CoinSharesNFTAI, aggregates different sets of data to provide a user with what it determines is a fair price for a rotating list of top NFT collections on OpenSea, the most popular NFT marketplace.

To interact with the bot, you need to grab the OpenSea link for a particular NFT of interest and tweet this at the bot. In turn, the bot will respond with an estimated value.

CoinShares says the bot runs an algorithm every week to calculate the prices of “the freshest collections.”

Pricing NFTs is no easy task, the company tweeted on Thursday. Their value is volatile and millions of them are available on the market, from established projects like Bored Ape Yacht Club to more obscure artists with no trading history.

According to the bot’s research paper, the algorithm builds upon the hedonic model to construct a price index from “thousands of NFT transaction records.” Its data focuses on Ethereum NFTs and uses Opensea’s official API to download the properties and past sales of certain NFT collections.

By Thursday afternoon, a number of people had tweeted at the bot, with the bot spitting out numbers that in some cases were much lower than the current best offers being made on OpenSea. Several users expressed scepticism of the tool’s accuracy when the estimated value of their owned NFTs came back lower than expected.

A spokesperson for CoinShares said that while NFT pricing might seem mysterious, its prices are driven by ‘many factors’ such as hype, rarity traits and real-world utility.

Some of these attributes are quantifiable – even hype is not as elusive a factor as it might seem, the spokesperson said. To evaluate the hype of a specific collection, we can count its followers on social media platforms, as well as the volume and value of past transactions. The same applies to rarity within a collection, by looking at the attributes of the asset.

An NFT collector may rely on market research or follow sentiment on social media to get a feel for each NFT’s value, but they might not put a specific number behind it, the spokesperson added. Our model accesses the same data but uses complex mathematical operations to make the best price prediction possible.