Instead of fragmented records, imagine a single timeline of your health where every data point (genome, image, questionnaire) is a "commit." This software development analogy provides a powerful model for tracking biological changes longitudinally and enabling comparisons against previous "versions" of yourself.
The medical industry is ignoring the threat of post-quantum computation. Adversaries are likely capturing encrypted health data today, planning to decrypt it once quantum computers are viable. This creates a hidden, time-sensitive risk that requires a fundamental rethinking of data security now.
The current model burdens hospitals with perpetual data storage liability. Enigma Genetics proposes offloading data ownership to individuals, who then grant access. Hospitals and pharma would pay for access as needed, transforming a costly institutional liability into a controlled, patient-centric transaction.
Enigma Genetics avoids large-scale models by assigning an individual AI to each user. This AI starts fresh and learns incrementally, avoiding the need to process vast historical datasets. This specialized approach is reportedly 1% the size of competitor models while maintaining high diagnostic accuracy.
We may not need to know *why* a biological error occurred. By having a "healthy version" of an individual's biology on record, future therapies could focus on simply reverting genetic or cellular states back to that healthier baseline, even if the underlying disease mechanism isn't fully understood.
Founder Ken Clark's frustrating experience with a persistent post-surgical infection, where his medical data offered no answers, directly inspired the idea of creating a "reversion" state—a healthy baseline of one's biology to compare against over time, much like version control in software.