We believe that software systems should be able to exchange data reliably, even under the most complex circumstances. Our discoveries in Categorical Mathematics sparked our vision for universal data interoperability and our mission is to bring it to the world.
Conexus develops technology, provides solutions and delivers services that enable data architects and IT leaders to overcome seemingly impossible challenges related to large scale data integration. When data complexity is high Conexus can dramatically reduce the costs and risks of consolidating and interoperating across data sources.
Born from MIT and built upon breakthroughs in Category Theory, Conexus technology approaches data integration differently. The technology enables an incremental “bottom-up” approach to data integration where the optimal master data model is discovered, not designed. The result is faster data integration that is more reliable and adaptable to change.
Founded by Eric Daimler, David Spivak, and Ryan Wisnesky, our team has a rich history in data science and Category Theory. We bring a high attention to detail and mathematical rigor to the work we do, so that you can trust the conclusions drawn from your data. We take pride in building solutions that help our clients achieve new outcomes and make better use of their data at the largest scales.