The problem Flowthentic solves

Flowthentic addresses a significant issue in the digital world: reliably verifying user identity in a manner that ensures both security and user privacy. In Web3, sometimes it's essential to have a system that can attest to the authenticity of users, particularly for applications that may need some degree of uniqueness.

Flowthentic solves this problem by allowing users to create a verifiable profile via a registration process that employs facial recognition and stores hashed personal data on the blockchain. These profiles, which can't be duplicated due to the uniqueness of the stored data, act as a secure and reliable form of identification.

A good use-case for Flowthentic could be in the context of voting systems, where ensuring one vote per person is crucial. By tying a vote to a verifiable, unique profile, it can help ensure the integrity of elections or other voting processes, ensuring that they are fair and representative.

Furthermore, Flowthentic protects user privacy by storing hashed personal data and encrypted images, making it difficult for malicious entities to misuse this information. As such, Flowthentic makes it safer and easier to verify user identity in a digital environment, opening up new possibilities for applications that require strong, reliable user authentication and uniqueness.

Challenges I ran into

During the development of Flowthentic, I faced some challenges that thankfully I managed to overcome.

One significant strugle I faced pretty soon into the start of the development was around the integration of the @onflow/fcl package with React Native. When I started development I realised that @onflow/fcl was adapted to web only and didn't support native applications, which caused issues in connecting a Flow wallet to my project.
However, the Flow team greatly helped me with this one. They pointed me towards a brand new repo that was a scaffold specifically designed to integrate @onflow/fcl with native apps. This scaffold effectively addressed my issues, facilitating the connection between the native app and the Flow blockchain.

Another major challenge I faced was while searching for a face recognition API service that could be used freely within the hackathon's context. I initially chose to work with the Azure Face API, but soon discovered that it didn't allow the usage of face recognition for my project. So I just used it for face detection and looked for other service that could provide facial recognition.
After some research, I turned to RapidAPI and PresentID. Through RapidAPI I accessed PresentID api which did exactly what I needed, it has a simple to use face recognition feature that ensured the successful implementation of Flowthentic.