Introducing the ioModel ML Platform

From concept to model to market.

ioModel Overview

ioModel is designed to provide existing analytics teams access to powerful machine learning models without having to write code, significantly reducing development and maintenance costs. Furthermore, analysts can then validate and understand the efficacy of models developed on the platform using well understood and proven statistical validation techniques. The ioModel Research Platform will do for machine learning what the spreadsheet did for general computing.

Our commitment to open development

The ioModel Research Platform is developed entirely using open source technology and is itself available (without support or warranty) under the GPL License on GitHub. We invite our community to collaborate with us on the roadmap, development, and governance of the Platform. We’re committed to working openly and transparently to drive forward analytics, modeling, and innovation..

ioModel can be used by engineers, data scientists, business analysts, product owners, and executives.

ioModel Workflow

Using ioModel, analysts can very rapidly move through every stage of the research and development process without writing code. Come with your understanding of analytics and domain knowledge and we’ll handle the repetitive coding behind the scenes.

The worlds of analytics and AI are about to converge and change forever

A new AI winter is not coming. Rather, firms that can capitalize on newly available technologies will be able to move faster and deliver more value than their competition. New branches of artificial intelligence like machine learning have evolved rapidly over the last 10 years but have traditionally required sophisticated teams consisting of data engineers, data scientists, and software engineers to effectively develop new insights and models.

ioModel challenges this traditional approach by putting the power of machine learning in the hands of subject matter experts directly, unlocking the potential for more rapid innovation at a significantly reduced cost with higher reliability. Rather than waiting for extracted data, relying on engineering teams to deploy and monitor models, and slow, costly development iterations, companies can now directly rely on existing subject matter experts and analysts to understand data and develop and deploy sophisticated models.

Rapid Deployment

Every machine learning model developed in ioModel is instantly available to your development teams via a RESTful API. Furthermore, your teams will be able to monitor the use of each model in real time and deploy additional model versions in order to easily understand impact and A/B test your results.