We’re a hybrid team of computer scientists and bioinformaticians committed to enabling scientists with a stellar platform for scientific data management and scientific computing.
While we started with multidimensional array database technology from Turing Award laureate MIT Professor Mike Stonebraker’s lab, we’ve advanced way beyond that.
We’ve spent years working closely with users to deliver an integrative analytics software platform that lets scientists focus on the science, not the computer science, to get answers to big questions fast. We help cut the daily science friction arising from wrangling complex multimodal datasets, orchestrating distributed computing, and ensuring reproducibility.
The result is a contemporary tech stack that addresses the need for easy-to-use front end APIs and GUIs that seamlessly handle all kinds of data—structured data, specialty file formats, unstructured data, graphs, and images—from thousands of data sets, public and proprietary.
Some of the late night members of our team.
We’re partners, not vendors. We’re really proud of our role working together, enabling Computing for Cures.
Build scientific and commercial value faster with a science-ready platform
Here’s what top pharma and biotech users are saying:
“storing scientific data as vectors makes sense”
“the most advanced solution we have to bring together multiple data types and give easy access across all to researchers”
“transforms the pace of our daily research”
“none of this is possible without your platform”
About Our Name
How did we come up with our name, Paradigm4? Well, we’re all about data-intensive discovery on massive data sets or massive collections of smaller datasets. Conceived by Jim Gray, you can read about the fourth paradigm, along with the preceding three paradigms: experimental, theoretical and computational here.
To channel Freeman Dyson, “New directions in science are launched by new tools much more often than by new concepts.” For the Life Sciences, new tools encompass both new data generating instruments and data collection initiatives as well as next generation software to combine and mine that data in unique ways.
And channeling Steve Jobs—with our platform, we aspire to enable scientists to “think different”, to do breakthrough science by giving them the ability to ask and answer bigger and more complex questions of their data more easily and more cost-effectively.
Importantly, working in partnership with our users, we will continue to expand the analytical, computational, and machine-learning capabilities that will help drive their innovation. As vendors introduce new technology and toolkits, the research community is quick to embrace and exploit what becomes the ‘new normal’. In turn, as they solve their problems, new information is generated, new tools and methodologies are developed, and the cycle of discovering ‘new directions’ repeats again.