Prodigy - Efficiently define, train and evaluate custom AI systems.

Prodigy Efficiently define, train and evaluate custom AI systems.

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#annotation
#data labeling
#Machine Learning
#NLP
#computer vision
#custom models

What is Prodigy?

Prodigy is an extensible annotation tool designed to facilitate the development of custom AI systems. It allows users to define classification schemes with real-world examples, making it possible to train and evaluate machine learning models efficiently, with no machine learning expertise required.

This developer tool runs entirely under the user's control, ensuring data privacy and security. Users can download and run it locally or adapt it to their infrastructure needs. The models produced are owned by the user, without any vendor lock-in. Prodigy offers powerful built-in workflows and extensive customization options, enabling users to create bespoke data feeds and interfaces.

Features

Information Extraction: Get structured data from text.
Language Model Training: Train and fine-tune models.
Computer Vision: Classify and segment images.
Audio & Video: Classify and segment AV data.
Prompt Engineering: Develop better LLM prompts.
Custom Workflows: Fully customize your experience.
Data Privacy: Runs entirely on your own machines
Customization: Define fully custom data feeds and interfaces.

Use Cases

Financial data analysis and risk assessment.
Medical document processing and clinical note analysis.
Multi-media data management and content creation.
Legal text analysis, contract review, and compliance.
Dialog system development and user interaction analysis.
Academic paper processing and corpus creation.

FAQs

What makes Prodigy different from other annotation solutions?

Prodigy is a downloadable developer tool for creating training and evaluation data for machine learning models. You can use Prodigy to build custom AI systems specific to your use case that you can own and control. Prodigy is a Python package and library that includes a web application. You can customize Prodigy with your own Python functions, and mix and match frontend components to make your own annotation experience.
Is our data really private? How does it work?

Prodigy runs entirely on your own machines and never “phones home” or connects to our or any third-party servers. Once installed, you can even operate it on an entirely air-gapped machine without internet connection. All data and models you use and create stay entirely private and under your control.
Which models can I use and train with Prodigy?

Prodigy lets you train any models you can train in Python. It comes with first-class support for our NLP library spaCy via the built-in train recipe, as well as plugins for using and training Hugging Face models. It also integrates with the major Large Language Model (LLM) API providers out-of-the-box.
How customizable are Prodigy’s workflows and interfaces?

Prodigy allows for extensive customization. A range of built-in settings makes it easy for non-experts to customize the experience, and the developer API and SDK lets you integrate the tool into your existing workflows and build powerful extensions for custom use cases.
What expertise does my team need to use Prodigy?

Prodigy is designed as a developer tool and assumes basic familiarity with the Python programming language and the command line. We also provide extensive documentation and examples to help you get started. Once you’ve set up an annotation task, the web application makes it easy for anyone to create annotations, no programming experience required.