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Lamin

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Lamin

Open data framework for biology

lamin.ai
1-10
Healthcare

Company research

Public company, workplace, funding, and market signals

Overview

Lamin is an open-source, zero-lock-in data platform for biology and multimodal AI. It helps teams query, trace, validate, and govern complex R&D datasets with lineage, context, and memory; the core product is LaminDB, a lineage-native lakehouse for biological data.

Primary product

LaminDB, a lineage-native lakehouse / open-source data infrastructure platform for biological R&D

Founded

2022

Headquarters

Munich, Bavaria, Germany

Team size

1-10

Industry

Software Development

Sub-industry

Biological data infrastructure / data management for life sciences

Offices

Munich, Germany
New York City, USA

Business model

open-source software
SaaS subscriptions
enterprise/on-prem deployments
freemium

Funding

Stage

pre-seed/seed

Latest round

Seed · Sep 2022

People & investors

Leadership

Dr. Dr. Alexander Wolf

Co-Founder & CEO

Dr. Xiaoji (Sunny) Sun

Co-Founder & President

Frédéric Enard

Co-CTO & Founding Engineer

Richard Sriworarat

Founding Full Stack Engineer

Sergei Rybakov

Founding Principal Engineer

Investors

Aaron Kimball
Alec Nielsen
Dimension Capital
Jeff Hammerbacher
Oskari Saarenmaa
Y Combinator

Work & culture

Mission-driven, research-heavy, open-source culture focused on biology and reproducibility. Public pages emphasize zero lock-in, collaboration, and invitations to join the team, but no employee-benefit program is publicly disclosed.

Product & market

Pricing

Freemium with open-source core, self-serve SaaS plans, and custom enterprise/on-prem pricing.

Differentiators

  • —Lineage-native lakehouse for biology
  • —Open-source and zero-lock-in
  • —Built for files, tables, arrays, ontologies, and notes
  • —Supports biological data formats and registries
  • —Git-like branching, versioning, and traceability
  • —Zero-copy sharing across databases and storage
  • —Works across Python, R, shell, and Nextflow
  • —LaminHub adds collaboration and governance

Technology

Python
R
shell
Nextflow
Django ORM
PostgreSQL
SQLite
AWS S3
Google Cloud Platform
parquet
zarr
AnnData
MuData
SpatialData
Vitessce
GitHub
Git
LaminDB
LaminHub

Customers

Pfizer
Altos Labs
Ensocell Therapeutics
scverse
DZNE
Helmholtz Munich
Harvard
MIT
Stanford
ETH Zürich
Charité
University of Bonn
Mount Sinai

Scale & contact

Estimated revenue

approximately $3M ARR (public estimate)

Latest news

Scaling anndata training to the terabyte scale with annbatch

Lamin Blog · Jul 2026

Introduces annbatch, a high-performance data loader for terabyte-scale omics training, with reported loading speeds of 60k samples/second and an emphasis on scaling AI workflows in biology.

Simpler queries for the 2.5B transcriptional profiles of the Arc Virtual Cell Atlas

Lamin Blog · Jun 2026

Describes a database mirror and zero-copy, lineage-aware sharing for the Arc Virtual Cell Atlas, one of Lamin's larger public atlas integrations.

Re-engineering the PerturBench benchmarking tasks with data lineage

Lamin Blog · May 2026

Shows how Lamin re-curated PerturBench workflows with lineage tracking so datasets and evaluation can be traced back to their sources.

Managing spatial omics datasets with SpatialData & LaminDB

Lamin Blog · Apr 2026

Announces native SpatialData support in LaminDB for cross-dataset queries, validation, lineage tracking, and downstream model training.

An introduction to LaminR

Lamin Blog · Apr 2026

Introduces LaminR, the R package for traceability and reproducibility in data workflows.

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SourcesOfficial about pageHomepagePricingImprintContactDocs introductionDocs securityBlog indexGitHub orgLinkedIn companyAlex Wolf LinkedInSunny Sun LinkedInFrédéric Enard LinkedInSergei Rybakov LinkedInCrunchbasePitchBookThe Company CheckGetLatka

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