Annota AI vs Dataloop

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.

Dataloop is a paid, enterprise-first AI development platform for building AI applications. It supports unstructured workflows for images, video, text, JSON, LiDAR, audio, PDF, GIS, and multimodal data. Users can work with off-the-shelf or custom models, then version, experiment, compare, and fine-tune them. Drag-and-drop pipelines or the Python SDK can coordinate data, models, and human feedback, including RLHF and other human-centric tasks. A marketplace provides models, datasets, workflow templates, and reusable components. Integrations include Google Cloud Platform, Amazon S3, Microsoft Azure Blob, AWS ECR, Google Artifact Registry, and Azure Container Registry. Dataloop lists GDPR compliance, ISO 27001, ISO 27701, and SOC 2 Type II compliance, with AES-256 and TLS v1.2 encryption. Access controls include role-based permissions, SSO, two-factor authentication, and activity logging. Deployment can be on-premises or in private storage. Pricing is available through a specialist demo.