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What is Galileo ?
Galileo was started to unleash the power of unstructured data.
Galileo aims to build the best platform possible for ML Engineers and Data Scientists building and productionizing AI applications. Galileo helps users with Evaluation, Experimentation, and Observability of models, prompts, and data.
Galileo offers 3 products:
Galileo LLM Studio is a platform for building production-grade LLM applications. Whether you're prompt engineering, finetuning a model, or monitoring a model in production, LLM studio offers distinct modules to help you across the stages of application development. Our algorithm-powered insights are meant to help you get to high-quality LLM applications faster.
Evaluation bench for a Prompt Run of an RAG run
To learn more about LLM Studio and get to get started, check out:
Galileo NLP Studio supports Natural Language Processing tasks across the life cycle of your model development. Using Galileo for NLP you can improve your NLP models by improving the quality of your training data.
During Training and Pre-Training, Galileo for NLP helps you to identify and fix data and label errors quickly. Through Insights such as Mislabeled Samples, Class Overlap, Data Error Potential, and others, you can see what's wrong with your data in a matter of seconds, instead of hours.
Once deployed, Galileo for NLP helps you monitor your model in production. Through its drift detection features you can measure and improve your training dataset to continuously improve your models in production.
The Galileo Console for a Named Entity Recognition run
To learn more about NLP Studio and get to get started, check out:
Using Galileo CV Studio you can improve your Computer Vision models by improving the quality of your training data.
During Training and Pre-Training, Galileo for CV helps you to identify and fix data and label errors quickly. Through Insights such as Advanced Error Detection, Mislabeled Samples, Class Overlap, Data Error Potential, and others, you can see what's wrong with your data in a matter of seconds, instead of hours.
Once errors are identified, Galileo allows you to take action in-tool or helps you take these erroneous samples to your labeling tool or Python environments. Fixing erroneous training data consistently leads to significant improvements in your model quality in production.
A screenshot of a Galileo console showing a Image Classification run
To learn more about CV Studio and get to get started, check out:
Last modified 7d ago