Contact us.
info@velohelix.com
(503) 567-9733
10052 SE Schiller St
Portland OR 97266
VeloHelix
Automating the Future
Exploring Laboratory Automation through innovative solutions
About Us
VeloHelix is an interdisciplinary laboratory automation company committed to transforming the way research, diagnostics, and industrial labs operate.
We develop modular, scalable automation systems and intelligent software tools that streamline routine processes, enhance reproducibility, and enable real-time data integration across laboratory workflows.
Our Services
Automated Laboratory Systems: Design and deployment of scalable automation workflows for clinical and research labs
Bioinformatics & Data Integration: Development of custom pipelines for genomic data analysis, LIMS integration, and visualization tools
Precision Medicine R&D: Collaborative research on pharmacogenomics and biomarker discovery for targeted therapeutics
Consulting & Prototyping: Technical consulting on lab digitization, smart reagent tracking, and custom prototype development
Our Technology
VeloHelix develops integrated laboratory automation solutions that combine precision robotics, modular scheduling algorithms, and real-time data acquisition across molecular biology, analytical chemistry, and high-throughput screening workflows.
We specialize in bridging legacy instrumentation and data systems with modern digital infrastructure, enabling a phased transition toward scalable, IoT-connected platforms.
Our architecture supports interoperability with LIMS, ELN, and cloud-based analytics pipelines to ensure full traceability, compliance, and operational continuity.
Current Research
VeloHelix is actively developing modular automation frameworks for next-generation laboratories, with a focus on protocol digitization, dynamic resource allocation, and AI-assisted experimental design. Our current projects span automated nucleic acid extraction, smart reagent inventory systems, and scheduling engines for high-throughput instrumentation.
We collaborate with research institutions and translational labs to modernize legacy workflows, integrate sensor-based monitoring, and advance reproducibility through data-centric lab environments.