Annota AI vs MakeSense.ai
Annota AI
annota.aiMakeSense.ai
makesense.aiSide by side
| Figure | Annota AI | MakeSense.ai |
|---|---|---|
| Price from | €21.96/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 1 |
| Spec score · Image Annotation Software | 8.4 (#4) | 8.6 (#3) |
Plans
Annota AI
- FreeFree
- Pro€21.96 a month
- Team€29.28 a month
- EnterprisePriced on request
In their own words
Annota AI
Annota AI combines image annotation, document OCR and review, and AI tools in a web or self-hosted workspace. For images, Magic Select creates an object mask for review and Magic Annotate locates selected labels in an image or dataset. Users can draw and edit bounding boxes and polygons, use segmentation masks, and export images and annotations in COCO format; PNG and JPEG are supported. Document datasets accept PDF, PNG, and JPEG files. OCR extracts content page by page for checking and correction, with exports as a Markdown ZIP or an Obsidian-compatible LLM Wiki workspace. Compatible agents connect through MCP remote servers using Streamable HTTP and OAuth, while organization permissions and shared credits apply. The maker says infrastructure and models run in EU regions without external AI-provider APIs. Plans range from Free at free to Pro at €21.96 a month and Team at €29.28 per member per month; Enterprise pricing is by quote. YOLO training remains private beta and requires separate approval.
MakeSense.ai
MakeSense.ai is a browser-based tool for labeling photos and preparing datasets for computer vision projects. It supports point, line, rectangle, polygon, and label annotations, with model-assisted labeling through YOLOv5, SSD pretrained on COCO, and PoseNet. Users can load their own YOLOv5 models exported to TensorFlow.js format. Export options include CSV, YOLO, VOC XML, VGG JSON, and COCO JSON; imports include YOLO, VOC XML, and COCO JSON. The available format combinations vary by annotation type, and some are not yet supported. The project says images are not sent to a server and AI features run using TensorFlow.js. It works in a browser across operating systems, and documented local and Docker setups are available; Docker serves the application on localhost:3000. The project describes it as suitable for small computer vision deep-learning projects and dataset preparation. It was founded in 2019, is licensed under GPL-3.0, and credits Piotr Skalski as author and copyright holder. The Free plan costs nothing.