With the rapid increase in annotated data requirements, building AI powered interactive annotation tools is the need of the hour. We present the Toronto Annotation Suite, a unified web-based-platform that is built to be AI-first, with AI algorithms supporting each level of a modern data annotation pipeline. We will be demonstrating novel human-in-the-loop image annotation algorithms for instance segmentation (published at CVPR 2019 and various unpublished improvements) and tagging on images within the annotation suite. We will also be showing prototypes of our ongoing research on interactive video annotation, and interactive annotation of meshes from LiDAR (point clouds). We hope this will become a part of the ML practitioners toolchain to support quick and cheap custom data annotation, resulting in fast prototyping of algorithms. We will also be accepting sign-ups for the beta-release of the annotation suite at the conference.