SuperAnnotate: AI Data Annotation Platform

Key Features

• Custom Annotation UI

  A drag-and-drop builder for creating specific annotation interfaces and interactive workspaces.

• Multimodal Editor

  Editors for handling image, video, text, and audio data types within the platform.

• Expert Talent Network

  Access to vetted and professionally managed annotation teams for data labeling projects.

• Enterprise Security Compliance

  Supports SOC 2 Type II, ISO/IEC 27001:2022, GDPR, CCPA, and HIPAA standards.

• RLHF and SFT Support

  Capabilities designed for Reinforcement Learning from Human Feedback and Supervised Fine-Tuning datasets.

• Orchestration Engine

  A system for automating workflows and managing compute hour allocations.

Use Cases

• RLHF Pipeline Development

  Building large-scale preference datasets to align AI models using human feedback.

• RAG System Evaluation

  Using human data to evaluate the performance of Retrieval-Augmented Generation systems.

• Multimodal Model Training

  Labeling and curating datasets involving image, video, audio, and text for model training.

• SFT Dataset Creation

  Creating fine-tuning datasets to refine the performance of large language models.

• AI Agent Evaluation

  Reviewing the choices and responses made by AI agents to help improve accuracy.

Integrations

• AWS
• GCP
• Azure
• Databricks
• Snowflake
• NVIDIA
• IBM

FAQ

What types of data can SuperAnnotate handle?

The platform supports multimodal data, including image, video, text, and audio.

Does SuperAnnotate provide the people to do the labeling?

Yes, it offers an expert talent network of vetted and professionally managed annotation teams.

Which pricing plan is right for scaling projects?

The Pro plan is designed for scaling AI projects and offers SSO and a dedicated Slack channel, while the Enterprise plan is for high-volume projects with dedicated solutions engineers.