Automagical Version Control & Experiment Manager for AI
with just two lines of code
process tracking and collaboration
with leading frameworks
TRAINS IS FOR YOU
For teams or entire companies, TRAINS logs everything in one central server and takes on the responsibilities for visibility and provenance so productivity does not suffer. TRAINS records and manages various deep learning research workloads and does so with practically zero integration costs.
Use it on a daily basis to boost collaboration and visibility, or use it to automatically collect your experimentation logs, outputs, and data to one centralized server.
TRAINS is a full system solution (Server, Python SDK & Web UI) for AI experiment management & version control. TRAINS tracks and controls the experimentation process by recording and managing various deep learning research workloads. It does this by associating code version control, research projects, performance metrics, and model provenance.
We encourage you to use the best open source packages for your needs. There are quite a few excellent choices available for different problems in this space.
We designed TRAINS to be a complete open solution – including server, Web UI and Python SDK – that is dead-simple to integrate.
TRAINS was designed specifically to require effortless integration so that teams can preserve their existing methods and practices. Integrating your work into a TRAINS server requires, literally, two lines of code.
TRAINS is entirely open source and free to use. TRAINS includes two components. The SDK is released under Apache 2.0 and the Server is released under SSPL.
Yes. As long as you comply with the terms of the license, you are free to use TRAINS at no cost. For more information, refer to the licenses of TRAINS and TRAINS-Server.
allegro.ai provides an end-to-end platform and suite of tools for managing the full lifecycle of deep learning -based perception solutions. We serve some of the most demanding and sophisticated organizations.
However, deep learning as a widely adopted technology, is still in its infancy. Most organizations are only taking their first steps into this field and their efforts are limited in scope. For these organizations we felt a dead-simple-to-integrate experiment manager and version control would be a great solution to a problem all of them share once they start making some progress.
In order to provide our share as corporate citizens to help seed this industry and to democratize deep learning, we decided to develop and open source TRAINS.