When deploying and using machine learning models in teams, it can be difficult to keep track of individual models and to share important results with colleagues. Often, machine learning software either doesn’t support sharing at all or forces you to download static representations, such as images and text files, in order to share insights and experiments. Alchemite™ has long supported a transparent sharing approach that allows all users with access to a particular model to view its analytics, experimental designs and all other information. This has now been enhanced with shareable permalinks (“perma-” so that they don’t change and can be reused for as long as the model exists), allowing analytics, experimental suggestions, and results to be shared effortlessly with team members, while keeping all the benefits of full interactivity and context at your fingertips. The links can be shared however your team works best, such as over Slack/Teams, email, or in a presentation or report.