VeryAI Secures $10M to Introduce Palm-Scan Identity Verification on Solana

VeryAI has successfully raised $10 million in funding to develop a cutting-edge palm-scan identity verification system on the Solana blockchain. This innovative approach promises enhanced security for authentication methods, addressing the increasing risks associated with conventional systems.

Key Takeaways

VeryAI has raised $10 million to launch a palm-scan identity verification system.
The system utilizes smartphone cameras to capture palm scans, which are uniquely secure.
VeryAI targets B2B partnerships, enabling integration into various platforms like cryptocurrency exchanges and fintechs.
It employs advanced privacy technologies such as Zero Knowledge Proofs to enhance user security.
The company aims to improve defenses against deepfakes through a new collaboration with Northwestern University.

Main Content

Current authentication methods, including facial recognition, CAPTCHAs, and two-factor authentication codes, are becoming increasingly vulnerable due to the rise in synthetic data generation. Reports show that the average time for attackers to breach systems has increased by 22 percent since 2023, with hacks now occurring in an average of just 48 minutes.

VeryAI is addressing these challenges with its innovative palm biometric technology, which provides a unique form of identification that is rarely shared publicly. Users can simply utilize their smartphone cameras to perform palm scans without needing specialized equipment. Notably, VeryAI claims this method has a false acceptance rate of roughly one in ten million for single-hand verifications, significantly better than the one in one million rates typical of many facial recognition systems. When both hands are scanned, the false acceptance rate improves drastically to about one in one hundred trillion.

The company's business-to-business (B2B) model allows cryptocurrency exchanges, fintech companies, and other platforms to integrate palm verification into their existing authentication systems, charging partners based on the number of monthly account verifications. This system is designed to work with standard smartphone cameras, making it more accessible to a larger audience.

Built on the Solana blockchain, VeryAI registers palm-scan identities efficiently with the benefits of Solana's quick finality and low transaction costs. Anatoly Yakovenko, a co-founder of Solana, is also an angel investor in VeryAI.

To enhance privacy and interoperability, the platform employs both Zero Knowledge Proofs (ZKP) and the Solana Attestation Service (SAS). These technologies allow users to verify their identity across decentralized applications without disclosing personal data. Furthermore, VeryAI utilizes ZK compression, similar to Light Protocol, which ensures that only essential state roots are saved on-chain while verifying states off-chain, thereby reducing storage costs without sacrificing security.

Upon completing the verification process, the system generates an anonymous identifier that proves an activity occurred without linking it to a specific individual. VeryAI emphasizes that it does not store palm images; instead, it retains irreversible feature representations that cannot be reconstructed.

The leadership of VeryAI includes Chief Executive Officer Zach Meltzer, who previously scaled Galxe to more than 6,000 partners and 34 million users while developing identity systems like KYC frameworks, and Chief Science Officer Hua Yang, a palm biometrics researcher with over 50 publications and patents.

Additionally, VeryAI has enlisted Matthew Groh, an assistant professor at the Kellogg School of Management at Northwestern University and Principal Investigator of the Human-AI Collaboration Lab, as an advisor. The company is initiating a research partnership with the university aimed at enhancing human resistance to deepfakes and improving the identification of synthetic media.

The recent funding will propel the expansion of VeryAI's Proof of Reality platform, facilitating the development of more tools to differentiate between identities generated by artificial intelligence and those verifiable human users.