TrueFoundry Raises $2.3 Million in Seed Round  

by Kay Aloha Villamor in September 20th, 2022

TrueFoundry, a San Francisco, CA-based startup that automates repetitive tasks in the machine learning pipeline to allow data scientists and engineers to focus on higher-value, more creative tasks, announced that it raised $2.3 million in seed funding.

The round was led by Sequoia India's Surge, with participation from Eniac Ventures and angels such as AngelList co-founder Naval Ravikant, Deutsche Bank Global CIO Dilip Khandelwal, GitHub India head Maneesh Sharma, Greenhouse Software CTO Mike Boufford, and Kaggle founder Anthony Goldbloom.

The startup intends to use the new funds to expand its platform and hire more people. It has recently opened early access to its platform and is working with companies as beta customers. It plans to go public in the next one or two months. It is also looking for advisors to help promote and expand the platform's reach.

Company: Ensemble Labs, Inc.

Raised: $2.3M

Round: Seed Round

Funding Month: September 2022

Lead Investors: Sequoia India's Surge

Additional Investors: Eniac Ventures, Naval Ravikant, Dilip Khandelwal, Maneesh Sharma, Mike Boufford, and Anthony Goldbloom

Company Website: https://www.truefoundry.com/

Software Category: Machine Learning

About the Company: Founded in 2021 by former Meta executives Abhishek Choudhary and Nikunj Bajaj, as well as angel investor Anuraag Gutgutia, TrueFoundry provides tools for startups and small businesses to deploy and monitor machine learning models at the speed of large tech companies such as Alphabet and Meta.TrueFoundry serves customers with small data scientist teams and operates in sectors such as fintech, e-commerce, financial services, healthcare, and retail, among others. Its mission is to deliver positive value from machine learning by making it fast and scalable. TrueFoundry has 16 employees, primarily based in India.


Source: https://techcrunch.com/2022/09/19/meta-alumni-startup-truefoundry-seed-funding-sequoia-surge-machine-learning/





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