Molecula-Is A Data Virtualization Platform That Enables Humans And Machines To Make Better Decisions





Molecula is a Data Virtualization Platform that enables humans and machines to make better decisions. Enterprises trust Molecula to enable instantaneous, secure access to large, fragmented, and geographically dispersed datasets to support the most demanding Machine Learning (ML) and Artificial Intelligence (AI) workloads.


Molecula was founded in 2017 with a mission to enable humans and machines to make better decisions by making data AI-Ready. This will push us forward into the future where we can reliably leverage machine-led and machine-assisted decisions to unlock the ultimate human potential.

With four (4) out of five (5) decisions expected to be machine-assisted in the next decade, we are combating the data access issues that plague the space today. To our dismay, Enterprises are making decisions on only 1% of available data due to the complexity of retrieving and analyzing data across distributed sources and locations. Further, IT teams are using a patchwork of Hadoop Era tools to transform and copy data for use across their organizations. As business leaders continue to demand the acceleration of data to decision cycles, these practices are not holding pace.

With Molecula, Enterprises can use 100% of their data for decision making from a single data access point, the VDS (Virtual Data Source). Based on our open source project, Pilosa, Molecula provides real-time virtualized access to all data—irrespective of the source, how it is formatted and where it is physically located. A library of plugins further extend Molecula’s capabilities for fast data exploration through popular data science tools, train models more efficiently on datasets without sampling, and successfully put them into production in a way that scales.


In Spanish, molecula means molecule. A molecule is the smallest particle of a substance that retains the chemical and physical properties of the substance. Likewise, Pilosa is the smallest fundamental representation of data that retains the computational properties of the original (human-created) values, but with many orders of magnitude less volume and exponentially faster analyzability (by a machine), regardless of the location or storage system of the source data. This makes Molecula highly secure and portable, allowing decisions to happen where they need to happen whether those are local, remote or on the edge without the burden of moving or compromising the source. Similarly, a molecule of any given substance is the same whether it is being viewed at the atomic level or as part of a physical object we interact with every day.

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