Enterprise IT / AI
Model Deployment & Serving
What is Model Deployment & Serving?
Model deployment vendors aim to make bringing a machine learning model to production faster and less costly, positioning themselves as bridges between enterprise data science and DevOps teams. Vendors offer tools for machine learning deployment on Kubernetes as well as serverless technology that can be used to deploy AI in cloud and on-prem environments.
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Leaders are the most established service providers in the market and possess the breadth to address various customer needs.
See why these companies made it as leaders for Model Deployment & Serving. These companies include Algorithmia.
United States / Founded Year: 2014
Algorithmia gives developers the ability to turn algorithms into scalable web services with a single click. Application developers can then integrate the algorithm into their own applications with under 10 lines of code. Algorithmia hosts the web services, makes them discoverable, and enables algorithm developers to get paid for usage.On July 27th, 2021, Algorthmia was acquired by DatRobot. The terms of the transaction were not disclosed.
Known Partners
Known Customers
Key People
Kenny Daniel
Highfliers
Highfliers are the most innovative service providers in the market and possess the resources to address evolving customer needs.
See why these companies made it as highfliers for Model Deployment & Serving. These companies include Datatron.
United States / Founded Year: 2016
Datatron's real-time big data AI engine is complete with proprietary software that allows for enterprises to optimize real-time business decisions.
Key People
Jerry Xu, Harish Doddi
Outperformers
Outperformers are the most specialized service providers in the market and possess the expertise to address unique customer needs.
See why these companies made it as outperformers for Model Deployment & Serving. These companies include Seldon.
United Kingdom / Founded Year: 2014
Seldon Technologies accelerates the adoption of machine learning to solve challenging problems. The company democratizes technologies that were once the preserve of tech giants – and putting them in everyone's hands.
Known Partners
Reply, Google Cloud Platform, Red Hat, and 1 more
Key People
Alex Housley
Challengers
Challengers are the most promising service providers in the market and possess the agility to address emerging customer needs.
See why these companies made it as challengers for Model Deployment & Serving. These companies include Arrikto and Bentoml.
Greece / Founded Year: 2015
Arrikto develops machine learning solutions that enable the user's data science and machine learning operations teams to collaborate together to continuously build, train, deploy, and serve machine learning models with DevOps efficiency.
Key People
Constantinos Venetsanopoulos, Vangelis Koukis, Mark Sue, and 1 more
United States / Founded Year: 2018
Bentoml develops a simple yet flexible workflow empowering data science teams to continuously ship prediction services.
Key People
Bozhao Yu, Chaoyu Yang
What is Model Deployment & Serving?
Model deployment vendors aim to make bringing a machine learning model to production faster and less costly, positioning themselves as bridges between enterprise data science and DevOps teams. Vendors offer tools for machine learning deployment on Kubernetes as well as serverless technology that can be used to deploy AI in cloud and on-prem environments.
Selling a product or service?
Reach more buyers.
Your future customers are researching their next tech solution on CB Insights. Make sure they can find you.
Claim your CB Insights Profile