SmooSense provides a gallery view that turns any image folder into a visual grid, helping you rapidly browse, compare, and understand large collections of images without opening them one by one.

SmooSense integrates an interactive, tree-view JSON previewer designed to make complex data structures easy to understand at a glance. Instead of staring at raw text, you can visually explore the hierarchy of any JSON field:

• Expand or collapse dictionaries to reveal nested keys layer by layer.
• Handle large arrays effortlessly. SmooSense displays the array's total length and shows only the first 100 items, so you get context without overwhelming the UI.
• Search across keys and values using simple keyword queries, making it easy to locate the information you care about even inside large or deeply nested structures.

This gives you an intuitive, high-level understanding of your JSON data instantly, without downloading files or writing ad-hoc scripts just to inspect structure.

Parquet is a columnar, metadata-rich file format designed for efficient analytic workloads. Parquet stores schema information, column statistics, and row-group metadata directly in its footer. When you want to preview a Parquet file, such as listing columns, data types, row counts, or min/max values, you don't need to download or read the full file. We only needs to fetch the last few kilobytes of the object from S3, where the metadata and column statistics are stored. This makes it possible to inspect very large Parquet files almost instantly, because the preview is based entirely on pre-computed metadata rather than scanning the actual data.

In the example below, you are previewing a huge 7.9 GB parquet file, with 100 million rows and more than 100 columns.

Markdown offers a format that’s easy for humans to write and for LLMs to interpret. It’s a natural choice for maintaining data documentation and sharing it seamlessly with AI systems.