While LinkedIn is helpful for displaying people’s educational and professional achievements, there exists a world of self-taught tech 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 is trying to fill that gap by providing an AI-powered profile builder for developers who wish to create LinkedIn-like identity pages for themselves. This is done by using large language models to review the quality of the code in projects to which they contribute. The platform also takes into consideration of social endorsement and applies network analysis to see if a programmer’s work has been “liked” by other recognized experts.
The number of web3 developers has been surging despite the crypto winter, and naturally, Aspecta’s data reach extends to the blockchain world. Its algorithms take clues from how users’ wallet addresses interact with smart contracts and tag their types of activity accordingly, which, according to He, is an “easier” process than vetting, say, GitHub data because “on-chain data is more structuralized.”
Aspecta is currently integrated with GitHub, so when users sign in with their accounts on the code hosting site, they receive an automatically generated identity page with all their technical achievements that look sort of like a gamer’s trophy page. The platform has also included Google, Stackoverflow and MetaMask in its data sources and is in the process of onboarding Twitter.
Aspecta’s alpha version has attracted some 130,000 users on its waitlist. Investors have taken notice of its traction, and today, the startup announced that 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 backing Chinese entrepreneurs expanding globally, as well as crypto-focused HashKey Capital and Foresight Ventures. The startup also attracted several strategic investors that would potentially tap its identity service, including Galxe, Dorahacks, CyberConnect, Mask Network and P12.
Like many startups that work in the digital identity space these days, Aspecta finds itself drawn to the decentralized governance mechanisms of web3.
“We are essentially creating an identity ecosystem and we don’t think it should be managed by a third-party corporation. Rather, it should be managed by a DAO,” said Jack He, co-founder at Aspecta, in an interview with TechCrunch.
A DAO, or a decentralized autonomous organization, is run by rules encoded as a computer program that is controlled by the organization’s members rather than a central party. Members of the DAO own tokens that allow them to vote on key decisions. The concept was all the rage during the crypto bull run, attracting artists, entrepreneurs and investors to initiate their DAOs, but many have lost steam since the market downturn.
Aspecta’s DAO hasn’t been implemented, yet. He reasoned that talent insights unearthed by the platform’s AI will eventually generate revenues, which would be best divided based on community rules. That is, it wants to let its users, or data providers, decide how their data are used by data consumers, the parties that make use of their digital footprint.
Aside from serving programmers, the platform also targets organizations that can make use of digestible developer data through its “identity-as-a-service”. Hackathons, for instance, might find Aspecta useful as its ID system can not only help register contestants but also offer a look at hackers’ proficiency. Or if a company is hiring developers, it could use Aspecta’s data to get a quick overview of candidates rather than examine 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 aren’t readily presentable on existing professional networking sites. As such, the startup plans to apply its algorithms to examine the popularity of creators’ tweets or Youtube videos as well as use graph learning algorithms to spot fake reviews.
“You could fake Twitter following, but you can’t game Expecta’s algorithm,” said He.
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