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Human Feedback Management

The Human Feedback Management module collects and manages feedback from humans and AI agents, optimizing data annotation workflows and enriching chatbot interactions through real-time feedback.

Key Features

  1. Dataset Creation & Organization

    • Define new datasets and their schemas.
    • Align data structures with specific annotation tasks or NLP workflows.

  2. Question Management

    • Attach questions to datasets for feedback collection.
    • Support various question types (ranking, rating, labeling, multi-label, free text).

  3. Dataset Annotation

    • Visualize records for human and AI annotators.
    • Simplify the annotation process with an intuitive interface.

  4. Annotator Assignment

    • Assign tasks to human annotators or AI agents.
    • Distribute workload efficiently for faster turnarounds.

  5. Unification Strategies

    • Consolidate multiple annotators’ responses.
    • Ensure consistency and reliability by applying different merging strategies.

  6. Dataset Formatting

    • Convert data into specialized formats (e.g., DPO or QA templates).
    • Maintain compatibility for varied NLP tasks or external integrations.

  7. AI Agents

    • Create and manage AI agents for automated labeling and analysis.
    • Integrate external LLMs (e.g., OpenAI API) or native platform agents.

  8. Real-Time Feedback

    • Capture user responses during chatbot interactions.
    • Improve conversational quality by refining models on-the-fly.

  9. Cross-Platform Compatibility

    • Integrate with native or external chatbot systems.
    • Leverage the module’s feedback mechanisms to enhance any conversational AI setup.

Key Benefits

  • Efficient Dataset Management
    Easily organize and maintain annotation data for a range of NLP tasks.

  • Enhanced Annotation
    Equip human annotators and AI agents with robust tools to label, rate, or rank data.

  • Seamless Chatbot Integration
    Plug into both native and external chatbots (via Gen AI Studio) to gather feedback, refine models, and improve interactions in real time.

Next Steps