Kili Technology vs Prodigy — Comparison

Kili Technology

Build high-quality and trustworthy datasets to train, fine-tune, and evaluate your AI models. Complete with a robust annotation tool built for collabo

Kili Technology began as an idea in 2018. Edouard d’Archimbaud, our co-founder and CTO, was working at BNP Paribas, where he built one of the most advanced AI Labs in Europe from scratch. François-Xavier Leduc, our co-founder and CEO, knew how to take a powerful insight and build a company around it. While all the AI hype was on the models, they focused on helping people understand what was truly important: the data. Together, they founded Kili Technology to ensure data was no longer a barrier to good AI. By July 2020, the Kili Technology platform was live and by the end of the year, the first customers had renewed their contract, and the pipeline was full. In 2021, Kili Technology raised over $30M from Serena, Headline and Balderton. Today Kili Technology continues its journey to enable businesses around the world to build trustworthy AI with high-quality data. Without them, are we even human? We are one team; we help each other with candor, and we stand together to achieve common goals. We own and master our topics, we learn fast to improve individually and collectively. We are curious, we have a growth mindset, we learn to be one step ahead. Leadership begins with ownership. Ownership breeds accountability. We take ownership to make a difference. We are critical-thinkers, we take our decisions based on facts, metrics, data analysis, instead of intuition. We achieve a lot, with little. We love keeping things simple and focusing on what matters. We aim to have 10X impact for our customers and users. We obsessively seek for what would change our customers our users life, and work backwards to create the right solution. Kili Technology is the complete platform to build trustworthy, high-quality datasets for training, fine-tuning, and evaluating AI/ML models.

Prodigy

A downloadable annotation tool for LLMs, NLP and computer vision tasks such as named entity recognition, text classification, object detection, image

Prodigy is an extensible annotation tool that gives you a new way to build custom AI systems. Define your classification scheme with real-world examples rather than just prompts, and let powerful models assist – no machine learning experience required. Prodigy runs entirely under your control, making it suitable for even the strictest privacy requirements. You can download it and run it locally right out of the box, or adapt it to serve your infrastructure needs. The models you produce are yours as well, with absolutely no lock-in. 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. Prodigy integrates tighly with spaCy, but can also be used with any other libraries and tools. The library includes a range of pre-built workflows and command-line commands for various common tasks, and components for implementing your own workflow scripts. Your scripts can specify how the data is loaded and saved and even define custom HTML and JavaScript. The web application is optimized for fast, intuitive and efficient annotation. 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. 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. At the core of Prodigy’s developer experience are recipes , Python functions that describe a workflow. Recipes can implement custom data processing and model training logic, integrate with third-party or internal libraries and tools and provide reusable workflows for your team that can be run without requiring programming or machine learning expertise. Prodigy also allows combining interfaces to build fully custom solutions, as well as implementing your own interactive interfaces with HTML, CSS and JavaScript. 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. Prodigy is an extensible annotation tool that gives you a new way to build custom AI systems. Define your classification scheme with real-world example

Kili Technology

Prodigy

Kili Technology

Prodigy

Kili Technology

Prodigy