We’re on a mission to redefine the future of neural networks

Our foundational research paves the way for a new field of possibilities in AI, allowing models of all types to be smaller, more powerful, and capture more nuance than ever before.

Introducing Dark Matter, an embedding API with a unique objective function

We’ve developed a net-new machine learning algorithm that accounts for hidden relationships in your data.

By taking snapshots of the loss landscape and encoding them into embeddings that represent new dimensions in your data, we make these relationships clear for your model where they were previously considered noise.

The result is improved predictive accuracy of any model in any domain.

Feature Enhancement: a new step in the pipeline

Derived from a new statistical theory not present in the current literature, Dark Matter offers a faster path to superior model performance.

This technology constitutes a fundamental, new step in the data science pipeline that we call Feature Enhancement. It slots seamlessly in after feature engineering to learn how to create statistically optimal embeddings to train your model.

Feature Enhancement is just the beginning. This new technology will enable a range of downstream modeling capabilities that are not possible today, providing a platform for future innovation across the ML pipeline.

Our Vision

Ensemble aims to level the ML playing field, offering machine learning practitioners and researchers access to sophisticated modeling capabilities. We’re dedicated to rigorous scientific innovation that creates products that enable engineers and researchers to do more — augmenting their capabilities and intelligence.

Our Values

Stay Hungry

We never stop learning. We eagerly pursue innovation, owning our mistakes along the way.  We set goals with a bias to action. We are unafraid and unjudging of failure, in ourselves or others. We achieve.

Stay Smart

We are flexible in thought and agile in our actions. We iterate quickly, and adapt readily to change. We put our team’s goals above our own. We don’t live in the past, worry about the future, or indulge in wishful thinking. We stay present, centering our attention to the task at hand.

Stay Humble

We value emotional intelligence. We behave and speak with kindness and respect, knowing our actions impact others. We are mindful that our view is just one of many. And strive to see situations with clarity, free of bias or emotion.

Team

We are scientists and engineers working together to push the boundaries of machine learning.

Alex Reneau

Co-Founder & CEO

Zach Albertson

Co-Founder & COO

Dmitry Buslaev

Founding Full Stack Engineer

Zhongfang Zhuang

Senior ML Engineer

Xiang He

Senior ML Engineer

Alexander Albertson

Business Developement

Lydia Grossman

Chief of Staff

Advisors

Mark Nelson

Venture Partner at Madrona

Former CEO of Tableau

Barry Dauber

VP of GenAI Sales at Databricks

Former VP of Sales at MosaicML

Lars Lider

VP of Strategy & People at Hadrian

Former COO at Machine Sciences

Kim Verbonitz

Former Head of BD, Strategy & Ops at AWS

Former CRO at Fingerprint Digital

Join our team!

Come work at the frontier of machine learning and AI technology.

Research

Dive into our cutting-edge research.

Feature Enhancement: A New Approach for Representation Learning (Whitepaper)

Discover a novel approach to representing complex, non-linear relationships inherent in real-world data.

Feature Programming for Multivariate Time Series Prediction (ICML)

Learn about a new framework for automated feature engineering from noisy time series data.

Resources

Blog
Op-eds and thoughts on the state of machine learning and AI
Documentation
Developer support, API docs, quick-start guide
Published Research
Ensemble research, papers, and conferences

Backed by:

logo-Salesforce-Ventures-white
logo-motivate-venture-capital-white
logo-M13-white
logo-AMPLO-white

Ready for better model performance?

Get in touch to learn more and book a demo.

Join the Waitlist

Early Access Form