Daft
Data engine for AI workloads that processes multimodal data at scale.
What is Daft?
Daft is a data engine designed for AI workloads. It enables users to process various data types at scale, transforming raw data into training-ready datasets efficiently It provides powerful tools to help teams work more efficiently and achieve better results.
What are the key features?
- Multimodal data processing capabilities.
- Integrated CPU and GPU pipelines.
- Familiar Python Data Frame API.
- Managed UDF runtime for models.
- Lower memory usage compared to alternatives.
Who should use this?
- Data scientists working with large datasets.
- AI developers needing efficient pipelines.
- Companies managing multimodal data sources.
- Organizations requiring scalable data.
- Researchers analyzing complex data types.
How does Daft help with AI visibility?
Daft does not help with AI visibility. Instead, it serves as a powerful data engine designed for AI workloads, efficiently transforming raw multimodal data into training-ready datasets. Users can process various data types at scale, utilizing features like GPU inference alongside CPU operations. This improves discoverability.
