Intellomix
Privacy-first WGS genetic-wellness platform.
The problem it solved
Consumer DNA tests read ~0.1% of the genome and risk exposing identity. Intellomix reads the full genome into 400 wellness traits while never learning who the customer is.
Similar problems it can solve
Privacy-first health-data platforms, any anonymous-by-design processing of sensitive data, and report-generation pipelines from large scientific files.
Turns a single 30× whole-genome sequence into a 400-trait wellness report across nutrition, fitness, sleep, personality and predisposition — delivered as an app and a trilingual PDF, and built anonymous-by-design so the platform never learns who the customer is.
- Anonymous-by-design — identity stays at the partner lab; the platform sees only an opaque code
- Ephemeral WGS pipeline (FASTQ/VCF) → PDF + in-app 400-trait report, then raw genome is deleted
- .NET 7 API + MAUI app (Android/Windows), trilingual EN/RU/HY, in-region hosting
The product
Intellomix turns a single 30× whole-genome sequence into a 400-trait wellness report across nutrition, fitness, sleep, personality and disease predisposition — delivered as a cross-platform app and a polished trilingual (EN/RU/HY) PDF.
One platform, many components
It is a complete system, not a model: an ASP.NET Core API, a .NET MAUI client for Android and Windows, a dedicated translation service that localises the 400-trait catalogue across three languages, and a report web system with its own generation database — all on top of a GPU-backed genomics pipeline.
Privacy by design (the distinguishing strength)
Identity never enters the platform. The partner lab holds the name-to-code link; Intellomix only ever sees an opaque sample code, a genome and a report. Credentials are server-generated and delivered out-of-band, and raw FASTQ/VCF is deleted after the report — an ephemeral, anonymous-by-design processor.
Engineering & scale
A FASTQ/VCF → trait-calling → report pipeline over 400 traits, an ancestry layer adapted for under-represented Caucasus reference panels, in-region hosting for data residency, and a capital-light operating model targeting the Armenian, Russian and wider CIS markets.
Technology
.NET 7, ASP.NET Core, .NET MAUI (Android/Windows), SQL Server, and a GPU WGS/genomics pipeline.