LatchBio offers a code-free platform that enables biotechs to store, organize, and analyze large biological datasets efficiently, streamlining the data lifecycle from raw data to actionable insights. By eliminating infrastructure setup time and providing customizable workflows, LatchBio accelerates research and development milestones while reducing costs associated with data analysis.
Funding
$32.8M 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.
Founders
Product
Problem
Biotechnology companies face challenges in managing and analyzing large, complex biological datasets, often struggling with data silos, infrastructure setup, and the need for specialized bioinformatics expertise. This complexity slows down research and development, increases costs, and hinders collaboration among scientists.
Solution
LatchBio provides a unified, code-free platform that streamlines the entire data lifecycle for biotech companies, from raw data storage to actionable insights. The platform integrates a file system, database, workflow manager, and elastic compute environment, enabling scientists to store, organize, transform, and analyze data without extensive infrastructure setup or coding. By providing customizable workflows and pre-configured analysis notebooks, LatchBio empowers researchers to accelerate experiments, make data accessible to all team members, and reduce the time and cost associated with data analysis. The platform also offers mission-critical security features, including SSO authentication and access control lists, ensuring data integrity and compliance.
Target Audience
LatchBio primarily targets biotech companies, bioinformatics teams, and research organizations that need a flexible and scalable platform to manage and analyze large biological datasets efficiently.
Features
- Unified platform integrating file system, database, workflow manager, and elastic compute
- Code-free environment for data analysis, eliminating the need for specialized bioinformatics skills
- Customizable workflows for various biological assays, including NGS and protein engineering
- Pre-configured Jupyter Notebooks and RStudio environments with necessary dependencies
- Scalable compute resources that can be spun up and down on-demand, optimizing cloud costs
- Integration with existing infrastructure, including Illumina BaseSpace, Benchling, AWS, and GCP
- Open-source SDK for uploading custom workflows
- SSO authentication and access control lists for enhanced security