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Transform scientific data into discoveries
Mantle brings modern data engineering to the lab to help scientists turn insights into world-changing breakthroughs.
MantleBio provides a cloud-based data engineering platform tailored for life sciences, enabling laboratories to organize, analyze, and share biological data with reusable workflows and notebooks. It emphasizes no-setup cloud access, reproducible analyses, and collaboration across teams. The platform aims to accelerate data-driven discovery in biotech and academia.
MantleBio offers a single workspace to organize, analyze, and share biological data. It includes centralized data storage (Mantle Database) for data and metadata, Python notebooks designed for science (Mantle Notebooks), and no-code/low-code pipelines (Mantle Pipelines) accessible from a browser or Python SDK. Users can run ready-to-use workflows (e.g., bulk RNA sequencing, spatial transcriptomics, imaging analysis), scale pipelines from pipettes to petabytes, and collaborate with shareable links, searchable data, and reproducible environments. Integrations with Benchling, AWS, Nextflow, and GitHub facilitate workflows and data movement. The platform emphasizes a collaborative, traceable, and scalable environment that supports both code-enabled and no-code analytics.
Who itβs for: Biotech and life sciences researchers and teams (academic researchers, biotech labs, and similar organizations) who need data infrastructure to organize, analyze, and share biological data and workflows.
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CEO and Co-Founder of MantleBio, modern data engineering for biotech. Previously developed software at GRAIL, Arsenal Bio, and The Broad Institute. MIT Computer Science and Biology. 10+ years at the intersection of computer science and life science.
CTO and Co-Founder of MantleBio. Previously worked as a software engineer at Google, Arsenal Bio and GRAIL.
Our data platform helps scientists and computational biologists manage and analyze high-throughput experiments
MantleBio offers a data engineering platform for life science research and computational biology that centralizes multiomics data, automates routine analyses, and enables reproducible pipelines and auditable datasets for biotech teams, including no-code access and integration with existing systems.
From the original launch (Jul 2023) β may be outdated.
Formerly βDryBox Bioβ Β· why startups rename β

The AI Platform for Life Sciences Intelligence

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