# Daft

- **Website:** <https://daft.ai>
- **Primary alias:** `daft.ai`

## Description

Daft is a cutting-edge data engine designed to revolutionize data processing for diverse modalities and scales. With its unique ability to handle structured tables, unstructured text, and rich media—all through a single intuitive API—Daft eliminates the need for multiple tools, driving efficiency in data workflows. Built on a robust foundation of Python and Rust, it allows users to bypass the complexities associated with JVM while achieving impressive performance enhancements, including 20x faster start times. 

Daft excels in various applications, including large-scale document processing and content deduplication, all while offering seamless integration with existing machine learning workflows through popular libraries like PyTorch and NumPy. Its remarkable capabilities extend to data handling across cloud storage services and modern table formats, allowing easy access regardless of data location. With intelligent memory management and a commitment to reliability, Daft empowers organizations to process vast amounts of data efficiently, making it the preferred choice for leaders in AI and cloud environments.

## Industries

- 🖥 Computers Electronics and Technology
- 🖥 Artificial Intelligence and Machine Learning _(under Computers Electronics and Technology)_

## Links

- [github](https://github.com/Eventual-Inc)
- [twitter](https://twitter.com/daftengine)

## Logos & icons

- icon _(primary)_ — JPEG — [download](https://cdn.brandfetch.io/iduGd27YP-/w/400/h/400/theme/dark/icon.jpeg?c=1bxid64Mup7aczewSAYMX&t=1784907090947)

## Colors

| Name | Hex | Theme |
| --- | --- | --- |
| Matisse | #1f5da5 | accent |
| Black | #000000 | dark |
| White | #ffffff | light |

## Fonts

- var(--font-times-now) — asset _(custom)_

## Imagery

- banner _(primary)_ — JPEG — [download](https://cdn.brandfetch.io/iduGd27YP-/w/1500/h/500/idMwsbE0Z-.jpeg?c=1bxid64Mup7aczewSAYMX&t=1784907091072)

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_Source: <https://brandfetch.com/daft.ai>_
_See [/llms.txt](/llms.txt) for a full list of agent-readable pages, and [/auth.md](/auth.md) for how agents authenticate._