The future is intelligent. From image-recognition software used to instantly diagnose cancer in patients to voice assistants learning to understand our every question, product experiences in the future will be customized, contextually-aware, and purposeful -- in short, they will be intelligent. Driving this transition of product experiences from the static to the sentient are models; specifically, statistical or machine learning (ML) models.
In this intelligent future, models are new code. However, while the tools to develop production-ready code are well-developed, scalable, and robust, the tools and processes to develop ML models are nascent and brittle. Between the difficulty of managing model versions, rewriting research models for production, and streamlining data ingest, the development and deployment of production-ready models is a massive battle for small and large companies alike.
At Verta.AI, we are building software in the service of models and the data science and ML teams that develop them. We are starting on this journey by addressing the problem of model management -- how to track, version, and audit models used across products. We build upon our research at MIT CSAIL on ModelDB, an open-source model management system deployed at multiple Fortune 500 companies. The Verta platform extends ModelDB to support model deployment, analysis, and collaboration, enabling data scientists to manage models across their lifecycle.
If the mission to enable businesses to create intelligent experiences inspires you, join us.