FastScore v1.2 - We live to deploy your data science models

Garrett Long November 10, 2016

It's been a little while since we had a blog post, as we've been heads down on software development.  We've been working on improving FastScore with our partners and customers, as well as the input we are receiving from the market.  It's really exciting to announce FastScore v1.2 today, which marks the 3rd release in 6 months of the product.  The feature velocity is gaining steam, as are the demos.  

v1.2 brings a unified capability to deploy analytics from a variety of model producers including R, Python, and Java.  The release also includes new input/output stream type supports, and some pretty major performance improvement - 3-5x prior versions.  Check the detailed Release Notes for more information.

It's an exciting time in the analytics market - the number of model producers continues to grow, as do the use cases that can leverage data science.  FastScore continues to be data science language and data platform agnostic - if you can build a model, we can deploy it.  

Topics: analytic engines, analytics, data science, Deployment, FastScore, Model Deployment, scoring engine