Spiral is described as a multimodal data platform designed for use in advanced AI contexts, particularly where machines are the primary consumers of data. It addresses the needs of modern AI systems that require access to a wide range of data types at machine-scale throughput. The platform is positioned for scenarios where agents, rather than humans, interact with data at large scale, such as in observability and pretraining tasks that demand high-speed access to diverse modalities.
Spiral supports a variety of data types, including video, images, audio, embeddings, point clouds, sensor streams (such as LIDAR and IMU), tables, text, bounding boxes, segmentation, geospatial, and time series data. All these modalities are organized within a single project tree, making them addressable and manageable through one unified query language. The platform also features a unified permissions model to govern access and control across different data types.
It is designed to support the requirements of frontier AI, where pretraining and other large-scale automated processes need to efficiently access and process every modality of data.
There is also no mention of its pricing, licensing, or the identity of its maker.
Spiral sits in PulseGate's Databases (SQL, NoSQL, vector, graph) category. It focuses on managing and querying multimodal data at machine scale for AI applications. It is built as a B2B product for AI engineers and data teams. Spiral is available on the web.
Behind Spiral is Spiral, and the product first shipped in 2024. Key capabilities include multimodal data support, unified query language, and high throughput.
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