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Top 2 Scientific Data Management Systems Companies Under $1M Revenue (August 2026)

As of August 2026, Latka tracks 2 scientific data management systems companies under $1M in annual revenue. They have combined revenues of $880K and employ 8 people.

Every company below sells scientific data management systems to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.

What Scientific Data Management Systems Companies do

Scientific Data Management Systems (SDMS) are specialized software platforms designed for the storage, management, and manipulation of large volumes of scientific data. These systems cater to various scientific fields, including pharmaceuticals, biotechnology, and environmental science, facilitating the efficient organization and sharing of data generated by laboratory processes and instruments. Core functionalities typically include data cataloging, metadata management, compliance tracking, and integration with other laboratory systems to ensure data integrity and security throughout the research lifecycle. The primary use cases for SDMS involve streamlining the data management tasks of researchers and scientists, enabling them to maintain a structured repository of experimental data, laboratory workflows, and related documents. Typical features may consist of user-friendly data entry forms, search and retrieval capabilities, data visualization tools, and support for regulatory compliance. The common buyer personas for SDMS include laboratory managers, compliance officers, and data scientists who require reliable solutions to enhance data governance and streamline scientific research operations.

Companies
2
Revenue
$880K
Funding
-
Employees
8

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Top Scientific Data Management Systems Companies Under $1M Revenue

Showing 2 of 2 companies ranked by annual revenue.

1grit42 logo
grit42

Copenhagen, Denmark

We hate overly complex software. So we built grit42 grit42 was created to serve drug discovery labs that don’t want to get lost in the corners of an enterprise data platform, but do want to find a better way to manage data and compounds than keeping track of endless versions of spreadsheets. Our scientific data management platform is free and open source, and we offer a range of point solutions for research labs built on top of that. The founding partners of grit42 have spent a combined 60+ years managing data, compounds, and test animals at large pharma companies. So we get where you’re coming from, and where you want to go. And with grit42, we want to help you get there faster and easier.

Revenue
$660K
Year founded
2014
Team size
6
2Labric logo
Labric

San Francisco, California, United States

The data layer for scientific research

Revenue
$220K
Year founded
2025
Team size
2

Frequently asked questions about Scientific Data Management Systems Companies Under $1M Revenue

How many scientific data management systems companies under $1M in annual revenue are there?

Latka tracks 2 scientific data management systems companies under $1M in annual revenue. Together they generate $880K in annual revenue and employ 8 people.

Which scientific data management systems company under $1M in annual revenue is the largest?

grit42 is the largest, with $660K in annual revenue, founded in 2014.

How much revenue does a typical scientific data management systems company under $1M in annual revenue make?

The average scientific data management systems company in this list makes $440K a year, across 2 companies with reported revenue.

Who are the leading Scientific Data Management systems vendors under $1M in annual revenue?

Ranked by annual revenue, the leaders are grit42 and Labric.

Related Vertical Industry Software categories

All Vertical Industry Software SaaS categoriesEvery category we track inside Vertical Industry Software, each ranked by revenue.Browse every SaaS industryThe full A-Z of SaaS categories Latka tracks, from Scientific Data Management to everything else.

Inclusion Criteria

- The software must provide centralized management of scientific data from various sources, including lab instruments and third-party applications. - Must include robust metadata management capabilities to annotate and describe datasets effectively. - Should support compliance with relevant regulatory standards in the scientific field, such as FDA, ISO, or GLP. - The system should allow for data sharing and collaboration among researchers and teams. - Must enable version control and audit trails to ensure data integrity and traceability. - Not just a data storage solution; must also provide analysis and reporting functionalities. - Should facilitate automated workflows to minimize manual data handling and entry errors.