In today’s healthcare landscape, the increasing reliance on cloud computing raises significant concerns regarding data privacy and security, especially for sensitive genomic data used in diagnostics and research. This study explores the potential of Fully Homomorphic Encryption (FHE) for secure computations on encrypted data, preserving privacy without decrypting. The FHE prototype was developed in Rust to demonstrate FHE’s feasibility and performance in evaluating encrypted genotype data. This research demonstrates that FHE enables protecting sensitive genetic information without compromising the ability to perform computations in reasonable time frames, data sizes, and quality. It also lays the foundation for future advancements in data-driven personalized medicine, allowing individuals to be confident in proactive healthcare management to protect their genetic information. In contrast to previous research, this research focuses on the case of direct-to-consumer genotype evaluation and demonstrates the feasibility and effectiveness of FHE, providing valuable insights into the potential for broader adoption of this technology in the healthcare industry.