Lamin
Lamin is a healthcare IT company based in Munich, Germany, specializing in open-source data infrastructure solutions for biology. It offers tools for managing, analyzing, and transforming data across healthcare and biological research sectors.
Services
Lamin provides open-source data infrastructure solutions for biology, offering a unified way to manage data and metadata across various platforms. Services include a Python framework for data management and analysis, an API & UI for accessing and managing data, and support for custom schemas and migrations. Lamin also tracks data lineage, integrates with workflow managers like redun, Nextflow, and Snakemake, and validates and standardizes data with one-line API calls. These services are available on both free and enterprise plans, with the enterprise plan starting from $500/month.
Products
Lamin offers several key products including LaminDB, an open-source database interface similar to git repositories for creating and managing data instances, and LaminHub, a platform for collaboration on data projects. LaminDB organizes data across multiple instances and supports data transfers with zero-copy. LaminHub provides different tiers of services, with a basic option available for free and a Pro version included in the enterprise plan, which also features comprehensive support and advanced customization options.
Founders
Lamin was founded by Dr. Dr. Fabian Alexander Wolf. Under his leadership, the company has developed innovative solutions for managing biological and healthcare data, transforming it into validated, queryable datasets and analytical insights.
Locations
Lamin is headquartered in Munich, BY, Germany, at Ruth Drexel Straße 122, 81927 München. The company operates across various regions including Germany and Europe, and offers both remote and partly remote working options to accommodate a distributed workforce.
Healthcare IT
Operating within the healthcare industry, Lamin specializes in healthcare IT. The company focuses on integrating data management solutions with existing laboratory workflows, facilitating collaboration between dry and wet labs through a distributed data hub. Their open-source framework eliminates the need to wrangle queries across fragmented data lakes and laboratory systems, simplifying the management and standardization of experimental and public ontology data.