Striveworks, an Austin, Texas-based provider of machine learning operations (MLOps) for enterprise data science and analytics teams, announced that it closed $33 million in funding.
The all-equity round was led by Centana Growth Partners, a specialized growth equity firm that invests in fintech and related enterprise software, with participation from existing investors.
The funding will be used to expand the Striveworks team, bringing on more engineers, salespeople, and marketing professionals to help drive growth and increase capabilities to better serve their customers.
Striveworks aims to simplify the process with a user-friendly, no-code platform that manages the entire model lifecycle, making it more accessible and effective in fast-paced environments.
Striveworks CEO Jim Rebesco, said. “This new funding allows us to continue to build and refine our industry-leading MLOps platform to support our partners and enable them to efficiently manage the vast amount of data the world has to offer, bringing the platform to where the data and decisions are made. As we look to build on our existing presence by expanding and commercializing in new, highly-regulated industries, partnering with an established firm like Centana, with its own track record of success, was an easy decision.”
Striveworks' cutting-edge MLOps platform, Chariot, operates invisibly behind the scenes to make the model building, deployment, and remediation processes seamless. Chariot enables enterprises' data science and analytics teams to streamline the process of taking machine learning models to production and then maintaining, monitoring, and improving those models.
Company: Striveworks, Inc.
Round: Equity Round
Funding Month: June 2023
Lead Investors: Centana Growth Partners
Company Website: https://www.striveworks.com/
Software Category: Machine Learning Operations (MLOps) Platform
About the Company: Founded in 2018, Striveworks is a responsible MLOps for national security and other highly regulated spaces. The company's MLOps platform, Chariot, enables organizations to deploy AI/ML models at scale while maintaining full audit and remediation capabilities. The platform empowers users with a flexible and differentiated solution offering, including data labeling, model training, deployment, monitoring, and remediation.