streamline high-throughput labs
Automate Routine Analyses
Start a sequencing run, go grab coffee, and receive the results in your inbox.
Science is complex, and connecting scientific systems can be complicated. An Illumina sequencer can generate over 6 terabytes per run and processing the outputs requires joining together multiple systems and pipelines.
MantleBio enables automating the process from run to result. Consistent data processing frees up time, and makes it easy to compare results between runs, users, and instruments.
We connect to laboratory instruments to pull data into the platform.
We read metadata from Benchling, Notion, BaseSpace, and other systems and connect it to the data.
We configure custom triggers to run pipelines when data is ready for analysis.
We send you the report when the pipeline finishes.
make bioinformatics a blast
Scale from Analysis to Pipeline
We know what computational scientists love, and it's not debugging cloud infrastructure. Spend less time on Docker files and more time on science.
Developing a new computational analysis requires quick iteration. You're using Jupyter Notebooks, R scripts, and public pipelines to explore the data and test techniques. Then, when you find something that works, you want to try it on more data. And when the data starts pouring in, you want something you can run reliably with minimal hassle.
MantleBio supports computational biology at every stage of development, without managing cloud infrastructure or throwing code "over the wall" to a different team.
Capture ad-hoc analyses easily through an SDK, API, or CLI. Think of it like a lab notebook for computational biology.
MantleBio streamlines the creation of pipelines from analyses by automatically generating configuration. When it's easy to create a pipeline, why wait? Create pipelines early to speed up iteration and make testing traceable.
Pipelines can be run in batches, from code, and from no-code. When every scientist at the company can find the data and run the pipeline, computational biologists can take vacations without blocking progress.
jump-start the next ai project
Train Machine Learning Models
It's an exciting time for ML in life science. The volume of data in biology is staggering and growing, and AI is revolutionizing practically every industry.
However, machine learning researchers know that over 80% of an ML project is spent collecting and cleaning the data. This challenge is at its extreme in life science. Metadata is scattered across formats and systems, data from expensive experiments is irreplaceable, and uncorrected batch effects could drown out the signal.
There are incredible opportunities for leveraging ML in biotech, and MantleBio can help overcome the obstacles in the way.
MantleBio makes good data practices easy from day zero.
Interoperability tools and data transformation pipelines help structure past experiments and standardize the most stubborn biological data.
Access analysis-ready datasets from API, CLI, or SQL to connect to other ML tools.