Aspecta gets $3.5 million to build AI vetted coding profiles

While LinkedIn is useful for displaying people’s educational and professional achievements, there exists a world of self-taught technical talent whose skills are not so easily reflected on the networking site. Rather, their expertise is hidden in the lines of code they write.

Aspecta aims to fill that gap by providing an AI-powered profile builder for developers who want to create LinkedIn-like identity pages for themselves. This is done by using large language models to assess code quality in projects they contribute to. The platform also takes social approval into account and applies network analysis to see if a programmer’s work is “liked” by other recognized experts.

The number of web3 developers increased despite the crypto winter, and of course, Aspecta’s data reach extends to the blockchain world. The algorithms extract clues from how users’ wallet addresses interact with smart contracts and tag their activity types accordingly, which He says is an “easier” process than vetting, say, GitHub data because “on-chain data is more structured .”

Aspecta is currently integrated with GitHub, so when users log in with their account on the code hosting site, they receive an auto-generated identity page listing all of their technical achievements that looks like a gamer’s trophy page. The platform has also included Google, StackOverflow, and MetaMask in its data sources and is onboarding Twitter.

The alpha version of Aspecta has attracted about 130,000 users on the waiting list. Investors have taken note of the appeal, and today the startup announced it has closed a $3.5 million seed funding round that would allow it to launch the beta edition of its flagship digital identity product, Aspecta ID.

Key institutional investors from the round included ZhenFund, a venture capital firm known for supporting Chinese entrepreneurs expanding globally, as well as crypto-focused HashKey Capital and Foresight Ventures. The startup also attracted several strategic investors who could potentially leverage the identity service, including Galxe, Dorahacks, CyberConnect, Mask Network, and P12.

DAO board

Like many startups working in the digital identity space today, Aspecta is drawn to web3’s decentralized governance mechanisms.

“We are essentially creating an identity ecosystem and we don’t think it should be managed by a third party. Rather, it should be managed by a DAO,” said Jack Heco-founder at Aspecta, in an interview with businessroundups.org.

A DAO, or a decentralized autonomous organization, is governed by rules coded as a computer program controlled by the members of the organization rather than a central party. Members of the DAO own tokens that allow them to vote on important decisions. The concept was all the rage during the crypto bull run and took off artists, entrepreneurs and investors to launch their DAOs, but many have lost steam since the market downturn.

Aspecta’s DAO has not yet been implemented. He reasoned that talent insights unearthed by the platform’s AI will ultimately generate revenue, which is best distributed based on community rules. That is, it will being late users, or data providers, determine how their data is used by data consumers, the parties that make use of their digital footprint.

In addition to serving programmers, the platform also targets organizations that can tap into digestible developer data through its “identity-as-a-service”. For example, hackathons can be useful for Aspecta because the ID system can not only help register participants, but also provide a window into hackers’ skills. Or if a company hires developers, it can use Aspecta’s data to get a quick overview of candidates instead of scrutinizing their code line by line.

The next step for Aspecta is to target content creators who face the same dilemma as software developers: their achievements are not easy to showcase on existing professional networking sites. As such, the startup plans to apply its algorithms to examine the popularity of tweets from creators or YouTube videos, as well as using graph learning algorithms to spot fake reviews.

“You could fake Twitter followers, but you can’t play Expecta’s algorithm,” He said.