Strateos offers a robotic cloud lab automation platform that enables scientists to remotely design, execute, and analyze high-throughput experiments in drug discovery and synthetic biology. This technology addresses the inefficiencies of traditional laboratory workflows by providing scalable access to automated lab capabilities, significantly reducing hands-on time and increasing productivity.
Funding
$72.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
+7Founders
Product
Problem
Traditional laboratory workflows in drug discovery and synthetic biology are inefficient, requiring significant hands-on time and limiting scalability, which hinders the pace of scientific discovery. Access to automated lab capabilities is often restricted, leading to bottlenecks in experimentation and data analysis.
Solution
Strateos offers a robotic cloud lab automation platform that enables scientists to remotely design, execute, and analyze high-throughput experiments. The platform reimagines the laboratory as a smart data generation center, providing scalable access to automated lab capabilities. By controlling scientific instruments and laboratories remotely, users can schedule workflows and manage scientific data through an easy-to-use web interface and standardized APIs. This approach accelerates the path from idea to data, supporting faster scientific discoveries and therapeutic innovations.
Target Audience
The primary audience includes pharmaceutical companies, biotech firms, startups, academic institutions, and CROs involved in drug discovery, synthetic biology, and AI-driven research.
Features
- Remote control of automated cloud labs accessible from a web browser
- High-throughput experimentation for drug discovery, cell and gene therapy, and synthetic biology workflows
- Smart lab facility design-build services and lab control software
- Integration of chemistry, biology, and tissue analysis into closed-loop robotic labs
- Automated workflows for gene assembly, protein expression, purification, and screening
- AI-powered drug discovery capabilities for evaluating large databases and predicting new drug candidates
- Secure APIs for programmatic integration into existing data engineering pipelines and software systems
- Compliance with FAIR Data Principles for findable, accessible, interoperable, and reusable research data