Database with a graph structure

EV Biotech produces micro-organisms to develop products such as vanilla and plastic sustainably. That happens not only in a regular laboratory but also in a digital one, where every cell combination is tested before the real lab work begins. It produces large volumes of data from experiments, chemical reactions and simulations.

As EV Biotech grew, that data had to be stored correctly and to one standard from the start, as the basis for large-scale analyses and AI applications later on.

We developed a database built on a graph structure, with semantic search and various properties for storing and displaying data. That structure matches the nature of the data: experimental biotech data is inherently relational and complex in the way it branches.

After the database was delivered, a follow-up project started around a new data innovation, with EV Biotech's own customers as end users. Alongside the technology, ease of use is central to that work.