Modlee
Information Technology And Services, 450 Lexington Ave, New York, 10017, United States, 1-10 Employees
Phone Number: +13*********
Who is MODLEE
There are more than 10 million annual ML experiments in R&D today, more than 100k skilled workers in data science and ML R&D, and more than $20B spent annually on wages alone for ML Profe...
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Headquarters: 450 Lexington Ave, New York, New York, 10017, United States
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Date Founded: 2023
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Employees: 1-10
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Revenue: $250 Million to $500 Million
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Active Tech Stack: See technologies
Industry: Information Technology and Services
SIC Code: 7372
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NAICS Code: 513210 |
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Frequently Asked Questions Regarding Modlee
Answer: modlee's headquarters are located at 450 Lexington Ave, New York, 10017, United States
Answer: modlee's phone number is +13*********
Answer: modlee's official website is https://modlee.ai
Answer: modlee's revenue is $250 Million to $500 Million
Answer: modlee's SIC: 7372
Answer: modlee's NAICS: 513210
Answer: modlee has 1-10 employees
Answer: modlee is in Information Technology and Services
Answer: modlee contact info: Phone number: +13********* Website: https://modlee.ai
Answer: There are more than 10 million annual ML experiments in R&D today, more than 100k skilled workers in data science and ML R&D, and more than $20B spent annually on wages alone for ML Professionals. However, given limited tools these experiments are slow, redundant and tedious. ML engineers and data scientists must perform many experiments before arriving at an ideal model for a given task and discovering an ideal model, that satisfies a task, can even take months of time. Over 80% of trained models today are never even deployed. modlee is a generative AI that suggests ideal models, bypassing the tedious and expensive experimentation process. Our vision is to not just improve the way organizations develop machine learning but to create a new asset-class for organizations to own their process for arriving at the best models. We want to transform the ML R&D process and significantly accelerate the time to model deployment.
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