Ensemble, a San Francisco, CA-based enterprise machine learning startup, raised $3.3m in seed funding.
The round was led by Salesforce Ventures with participation from M13, Motivate, and Amplo.
The company intends to use the funds to expand operations and its development efforts.
Co-founded by Alex Reneau, and Zach Albertson, Ensemble allows organizations to train accurate ML models on limited, sparse, and high-dimensional data without extensive feature engineering by creating statistically optimized representations of data.
The team has developed a net-new representation learning algorithm that learns to approximate hidden relationships in data by outputting embeddings, distilling signal from noise to allow ML models to achieve state-of-the-art performance — even with limited, sparse, and high dimensional datasets.
The company’s product, Dark Matter, is an embedding model that creates rich representations of data to make any model, in any domain, higher-performing across metrics. Feeding model learned, statistically optimal features for task improves performance metrics, reduces engineering time, and frees teams up to focus on experimentation.
FinSMEs
30/09/2024