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Striveworks Raises $33 Million for MLOps Tools
Striveworks, a startup building MLOps tools to handle the building, training and cleaning of machine learning models has raised $33 million in funding from Centana Growth Partners. This represents the first outside funding for Striveworks, which has enjoyed annual growth of 300% over the last two years. Striveworks intends to use the new funds to further develop their product and business, as well as for hiring new employees.
A Booming Interest in Artificial Intelligence
The current funding round is an ‘opportunistic’ one, with Striveworks previously operating as a ‘capital efficient’ startup that relied on profits and existing investment for growth. Striveworks’ clients represent a range of verticals, including the financial and government sectors, heavily-regulated industries and national security applications, and imagery sectors including computer vision and satellite imagery. The company has partnerships with Microsoft’s Azure and Amazon’s AWS, and aims to address key problems encountered in machine learning model building and production.
The ‘Day-One Problem’
Striveworks aims to address issues in machine learning model building, starting with the ‘day-one problem’: building appropriate machine learning models to achieve target objectives. However, according to Striveworks CEO Jim Rebesco, the complexities start to emerge after the model has been built. Does it do what you expect it to do, and when you put it into production, does it continue to perform as you expect? We focus on what happens next,” said Rebesco.
The Importance of Analysis and Responsibility
Rebesco noted the importance of accountability and responsibility in AI and machine learning use. As these tools are becoming more ubiquitous, it’s essential to approach queries effectively. Striveworks tackles this challenge through its platform, Chariot, which prepares data, builds models and runs them in production through team collaboration, low-code features and the ability to integrate third-party tools.
Catering to Real Customers with 7-Figure Contracts
Investor Ben Cukier from Centana noted that Striveworks had a clear advantage over its competitors, as the business is being run very efficiently. Cukier added that Striveworks has achieved a rare level of scale without outside capital, with real customers and seven-figure contracts, and net retention numbers that would make other companies envious. Striveworks is yet to disclose its valuation.
FAQs
What is Striveworks?
Striveworks is a startup building MLOps tools that tackle problems encountered in building and training machine learning models. Clients of Striveworks include high-regulation industries, government and national security applications sectors and the financial industry.
What is Chariot?
Chariot is Striveworks’ flagship platform used for preparing data, building models and running models in production through team collaboration, low-code features, and the integration of third-party tools.
What is the ‘day-one problem’?
The ‘day-one problem’ refers to building appropriate machine learning models to achieve target objectives. Striveworks addresses this issue through Chariot, where teams collaborate to prepare data and build models that can run in production with third-party tool integration.
What makes Striveworks different from other MLOps startups?
Investor Ben Cukier highlights Striveworks’ clear advantage over other startups in the field, specifically that Striveworks has achieved a rare level of scale without previous outside capital, and as such has been catering to real customers and seven-figure contracts.
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