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Lamin

Open data platform for traceable, multimodal AI

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Lamin is an open-source, lineage-native, format-agnostic lakehouse for R&D data, built to help teams and AI agents query, trace, and govern heterogeneous datasets across storage formats and locations. It addresses the challenge of connecting laboratory results with models and experiments by providing a programmable memory layer that scales from personal projects to enterprise deployments, with support for biological formats and registries.

Key capabilities include lineage tracking across agents, notebooks, scripts, and workflows; a lakehouse supporting formats like Parquet, Zarr, AnnData, and SpatialData; unified records management for notes, LIMS, ELN, and ontologies; branching and versioning for datasets, records, and models; schema-based validation and annotation for FAIR datasets; and fine-grained permissions for humans and agents. Integrations include bio ontologies, git, Nextflow, Vitessce, and Redun, with extensibility through custom Django ORM-based plug-ins. It runs on Postgres or SQLite, supports local, S3, GCP, and Azure storage, and installs via pip or CRAN without Docker.

Lamin is designed for computational biologists, data scientists, and ML teams in academia, biotech, and pharma. It offers a free plan with open-source database features, a Pro plan with a hosted database and storage, a Team plan with organizational accounts and governance features, and an Enterprise plan for full on-prem deployment. Plans are billed annually, with Pro and Team offering free trials, and Team and Enterprise priced per seat.

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