Modin scales Pandas data workflows by changing a single line of code in a project.
Adala
Adala automates data labeling through an autonomous agent framework for organizing labeled datasets.

About Adala
Adala is an open source Autonomous Data Labeling Agent framework maintained by HumanSignal and hosted on GitHub. It is designed for data processing with a focus on data labeling tasks. Agents learn skills iteratively based on an environment, observations, and reflections.
Users provide a ground truth dataset to define the environment, then create and train skills such as classification. Skills can be configured with output requirements and constraints, and run in a runtime such as an LLM. The repository includes documentation, examples, tests, and Docker files, and it can be installed with pip and used as a Python library in notebooks with pandas DataFrames.
It suits people working in AI and machine learning who use Python, including AI engineers, machine learning researchers, and data scientists. Educators and students can also use it for teaching, projects, and research on agent-based data processing.
Key features
- Autonomous agents for data labeling tasks
- Environments defined with ground truth datasets
- Configurable skill outputs with set constraints
- Skills deployable across multiple runtimes
- Python notebook use with pandas DataFrames
- Installation via pip and Docker files
- Open source code with docs and examples
- Usable in Python notebooks with DataFrames
- Configurable outputs and extensible runtimes
- Requires Python and programming knowledge
- Requires setting an OpenAI API key
- GitHub repository format suits developers
Adala at a glance
- Website
- github.com/HumanSignal/Adala
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
Adala alternatives
Tools and sites you could use instead, ranked by how closely they match.
Ultralytics supports detection, segmentation, image classification, pose estimation, and tracking across YOLO model versions.
H2O AutoML automatically generates features and selections, with a no code AutoML offering.
The LightGBM framework uses gradient boosting for ranking, classification, and other machine learning tasks.
pytorch tabular provides a unified framework for deep learning models on tabular data.
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
Popular in AI Data & Analytics
Well-known listings from the same topic.
Adala FAQ
What is Adala?
How do I install Adala?
What do I need to use Adala?
Is Adala open source?
Tell us and an editor will check it.
Claim the listing and suggest updates yourself. An editor checks every claim first.












