We are building a future where all people and computers can share an understanding of the data they interact with. We are building universal data interoperability.
Conexus develops technology, provides solutions and delivers services that enable big data system architects, data warehouse leaders, and chief data officers to overcome seemingly impossible challenges related to large scale data integration and migration. When data heterogeneity is high, and consequences are severe, Conexus can decrease your costs quadratically.
Born from MIT and built upon breakthroughs in Category Theory, Conexus technology approaches data integration differently. It changes and migrates data in a mathematically universal way, which ensures zero degradation and full transparency into data provenance. An embedded automated theorem prover eliminates risk of human error in ETL design decisions.
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.