Prodigy AI

Use Case 1: Private Information Extraction from Sensitive Documents

Problem: Organizations in healthcare or finance need to extract structured data from sensitive records but cannot use cloud-based AI due to strict privacy regulations.
Solution: Prodigy runs locally and on air-gapped systems, allowing teams to annotate data and train models without any information leaving their internal servers.
Example: A hospital extracting clinical notes from medical documents while maintaining full HIPAA compliance.

Use Case 2: Human-in-the-Loop Model Fine-Tuning

Problem: Standard LLM prompts often fail to capture specific nuances required for niche industry tasks, leading to inconsistent outputs.
Solution: Users can use Prodigy to label real-world examples and use them to fine-tune models like spaCy or Hugging Face, creating a custom AI that follows exact requirements.
Example: A legal firm training a model to specifically identify and categorize risk-related clauses in complex insurance contracts.

Use Case 3: Efficient Multi-media Content Classification

Problem: Sorting and segmenting vast amounts of audio, video, or image data is traditionally labor-intensive and expensive.
Solution: Prodigy provides optimized interfaces for computer vision and audio-video tasks, allowing for efficient classification and segmentation through custom workflows.
Example: A media archive classifying thousands of hours of historical footage by identifying specific objects and speakers.