Helix operates a population genomics platform handling terabytes of sequencing data weekly for health systems, life science companies, and payers. The tech stack reflects a dual engineering identity: a modern frontend (Next.js, React, TypeScript) paired with heavy-duty genomics infrastructure (Nextflow, OMOP CDM, Apache Airflow, Go, Python, C++). Current project focus spans AI-enabled workflows, therapeutic data models, and clinical integration—all moving through a highly regulated environment. Hiring is senior-weighted and concentrated in engineering and data, signaling scaling pressure on pipelines and analytics rather than market expansion.
Notable leadership hires: Head of Customer Service
Helix enables health systems, life sciences companies, and payers to integrate genomic data into patient care and drug development workflows. Founded in 2015 and based in San Mateo, the company operates as a private organization with 51–200 employees across engineering, data, product, marketing, and sales teams. Core work involves next-generation sequencing, bioinformatics analysis, and population health insights. The company faces ongoing challenges with clinical adoption of genomic findings, regulatory compliance, and the computational scaling required to process large-scale genomic datasets weekly.
Helix runs Next.js, React, and TypeScript on the frontend; Go, Python, Java, C++, and C# for backend services; Apache Airflow and Nextflow for genomics pipelines; PostgreSQL for data; and AWS for infrastructure. They also use OMOP CDM for clinical data standards.
Current projects include genomic data pipelines, AI-enabled operations workflows, therapeutic area data models, web applications for genomic analysis, dashboards for health systems, and population health insights for life science companies.
Helix's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.