Skip to content

About Featrix

LLMs and Generative AI have kicked off an unprecedented wave of innovation. Early applications of GenAI focused on processing previously untapped unstructured data, yet structured data still drives a majority of the world economy. Current approaches to predictive analytics on that structured data tend to be hand-crafted labors of love, which simply won't scale going forward.

featrix-vectors

Above: a set of vector embeddings during training with Featrix.

That's why we started Featrix—to tackle the need for automated analytics and predictive AI for the next generation of computation. Vector-based computation opens up new possibilities, and not just for unstructured data. Our goal is to make predictive AI models on structured data as easy as LLMs have made answering questions in natural language.

As the foundation, we developed the Featrix AI SDK, which brings the power of vector embeddings to tabular data. At its heart is our Featrix Analytical Pre-trained Transformer (APT), which combined with either off-the-shelf or custom models delivers a cutting edge AI system and developer experience that requires no additional tooling for data processing or model monitoring.

Building on our SDK, we are providing solutions for predictive analytics, and we have started with lead qualification and website personalization. We take care of it, from end to end.

Our founders: Deep B2B software experience

Headshot-Mitch43

Mitch Haile

CEO & cofounder

Mitch has been delivering data solutions to the midmarket and enterprise for over two decades. With deep experience in compression, ETL, backup, virtualization, data monitoring, Mitch has over 36 issued patents and was among the first ten engineers at both Data Domain and SnapLogic. He later founded Pancetera (sold to Quantum). Mitch has run marketing, product management, and engineering teams.

pawel_headshot

Pawel Zimoch

CTO & cofounder

Pawel dropped out of his MIT PhD in mechanical engineering to follow his love of entropy from thermodynamics to information theory to machine learning. He did get his Masters from MIT and an undergrad degree from Harvard, both in mechanical engineering. Pawel previously worked at Gamalon, a natural language processing AI company where he supported the AI efforts at large enterprise accounts for the company, including some of the Fortune 500.

Company news