Investing in Fair Math
Fair Math stands at the forefront of privacy computing by offering a suite of tools that simplify the development of fully homomorphic encryption (FHE) applications and actively promoting the adoption of FHE applications
Blockchains in their current state have made significant progress in scalability and user experience, but the privacy problem still has a long way to go. Early projects like Zcash and pioneered the use of ZKPs in private payments between individual private states, but ZKPs are not suitable for more complex compute where knowledge of shared private state is required to generate individual proofs.
Furthermore, as the complexity of proofs increases, we are driven toward relying on trusted third parties with more compute power to generate ZKPs. And those trusted third parties have to decrypt the encrypted data into plaintext to run computations over the data. This is an obvious limitation to privacy enabled solely by ZKPs.
Enter FHE. FHE is a cryptographic technique that allows computation directly over encrypted data — i.e., without decryption. FHE guarantees data privacy during computation, enhancing security for cloud computing and transacting sensitive information (e.g., PII, passwords, keys, etc.)
In short, ZKPs are not designed for data processing as is FHE. Rather, they specifically function to confirm the truth of a claim without revealing the data itself.
Among the existing solutions in the burgeoning FHE field, there is no universal and comprehensive library of FHE components for simplifying the process of developing FHE applications.
Fair Math is making this. Their approach requires addressing the challenges of (1) limited resources and (2) addressing requirements for a wide variety of components. To this end, they are actively attracting a large community of contributors to solve FHE problems as a collective.
They also launched FHERMA — a fully automated challenge platform like Kaggle for the FHE world — in collaboration with the OpenFHE. The main idea here is to take a community-centric, competition-based approach to solving challenging problems around FHE development. The end result: a robust and organized library of FHE components for application developers.
We love that they are doing all this with an open-source and community-oriented approach. Together, Fair Math and its growing community are building open-source products under fair licenses.
The company was co-founded by Gurgen Arakelov and Elvira Kharisova. Gurgen founded FHERMA and holds a PhD in Math/CS. He has 10+ years of experience creating privacy-preserving computing solutions for companies such as Samsung, Huawei, Intel, and Wheely. Elvira is a serial entrepreneur with 10+ years in cybersecurity.
We met Gurgen at an FHE event during Devconnect last year and were immediately impressed by his background and existing contributions to the FHE space through FHERMA.
After speaking about his plans for Fair Math in more detail, it became evident that there was a big opportunity for us to support a highly talented, technical, no-nonsense team in building out the future of the web3 FHE ecosystem. There are few teams like them who have the background and skillset to build a privacy solution like Fair Math.
We could not be more proud to be co-leading Fair Math’s pre-seed round to help Fair Math achieve escape velocity and become a vertical leader in its next phase of growth.
Welcome, Fair Math!
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