Case Study: Berkery Noyes boosts M&A analysis speed with Julia Computing

Berkery Noyes is using Julia for mergers and acquisitions analysis

Berkery Noyes, an independent investment bank serving middle-market entrepreneurs in information software, marketing services, and technology, needed a technology-enabled way to support its mergers and acquisitions advisory work. To keep up with innovative clients and manage a large proprietary database and workflow system, the firm turned to Julia Computing and the Julia language.

With Julia Computing, Berkery Noyes built on its integrated platform of CRM, email marketing, research, and workflow tools to speed up high-level scientific and numerical computing without rewriting code into lower-level languages. According to the CTO, Julia runs 20 times faster than Python, 100 times faster than R, 93 times faster than Matlab, and 1.3 times faster than Fortran, helping the firm continue investing in faster, more efficient M&A analysis.

Berkery Noyes

Keith Lubell

Chief Technology Officer