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💡 Common Use Cases

This page outlines the most common ways developers use Visionary.ai in real-world applications.

Whether you’re building a mobile app, a SaaS platform, or an internal tool, Visionary.ai can help you extract value from images in just a few API calls.

📱 Emotion Detection in Social Apps​

Use case: Enhance user engagement by detecting emotions in selfies or shared photos.

  • Use the /emotion endpoint to analyze facial expressions.
  • Tailor reactions, comments, or notifications based on the detected mood.
  • Example: If a user shares a smiling photo, send a “Happy Vibes Only” sticker.

🔞 NSFW Filtering for User-Generated Content​

Use case: Automatically block or flag inappropriate images uploaded by users.

  • Use the /nsfw-filter endpoint to detect explicit content.
  • Apply moderation thresholds based on your community guidelines.
  • Works well for forums, dating apps, social platforms, or file uploads.

🖼️ Metadata Extraction in Photo Management Apps​

Use case: Display detailed image metadata to help users sort, search, or tag photos.

  • Use the /metadata endpoint to extract:
    • Dimensions (width/height)
    • Format (JPEG, PNG…)
    • ISO, exposure time, geolocation (if embedded)
  • Helps create smart albums or filters by camera type or date.

🛡️ Internal Moderation for Enterprise Tools​

Use case: Ensure uploaded visuals are safe and compliant in B2B applications.

  • Integrate all endpoints for image vetting before publishing.
  • Automate rejection flows with NSFW or emotion thresholds.
  • Example: A CMS for marketing teams that prevents uploading disturbing visuals.

🧠 Pre-Filtering for AI Training Sets​

Use case: Curate image datasets for machine learning with quality and safety filters.

  • Use /nsfw-filter and /metadata before adding new samples to your training pipeline.
  • Avoid training on corrupted, unsafe, or low-quality images.
  • Ideal for ML teams building facial recognition, emotion tracking, etc.

🛠️ Combine Endpoints for Custom Pipelines​

Use case: Run multiple analyses in parallel to create rich, multi-layered features.

Example workflow:

  1. User uploads a photo
  2. Run /nsfw-filter
  3. If clean → Run /emotion + /metadata
  4. Use results to personalize experience or enrich metadata

🧪 Other Ideas​

  • Detect emotional trends over time from a user’s gallery
  • Auto-label images before cloud upload
  • Build a parental control feature in a gallery app
  • Enrich a visual chatbot with mood-aware responses

Need help implementing a use case? → Contact us at support@visionary.ai or check the Quickstart Guides