TL;DR: Fused is a versatile platform that serves as a code catalog, a parallel data processing engine, an app creation tool, a serverless HTTP endpoint generator, and an IDE.
Fused is a powerful and versatile tool that can do nearly anything with just Python. Its versatility is its strength, but it is also an obstacle. It's easy to walk about wondering: what, concretely, can Fused do for me?
Here are six concrete ways you can use Fused today.
TL;DR Jeff Faudi used Fused for real-time object detection on 50cm satellite imagery, displaying results as an interactive web map.
In this article I show how to create an object detection layer on 50cm imagery in realtime. It explains how to create a Fused User Defined Function (UDF) to load satellite image tiles to call an inference model, then publish it as an interactive map app.
In this video tutorial, I show a complete data app workflow in Fused. Starting with exploring the data in Fused, the tutorial walks through developing a UDF to serve the data, and then a Fused App to share results.
With Fused, this whole workflow takes just minutes from beginning to end. Fused helps me visualize the data at every step, iterate on my analytical logic, and finally publish a dashboard.
TL;DR Kevin used Fused to create a global vegetation segmentation layer without machine learning, displaying results as an interactive web map.
In an era where data-driven decisions are vital, accurate and scalable vegetation analysis plays a crucial role across various industries, from environmental monitoring to urban planning. While AI and machine learning have transformed image analysis, they often bring complexities and resource demands that aren't always practical for large-scale, real-time applications.
TL;DR Pachama uses Fused to create maps on-the-fly for their sustainability platform.
Pachama is a technology company that harnesses satellite data and AI to empower companies to confidently invest in nature. The engineering team at Pachama created a Land Suitability Tool to help landowners and project developers qualify parcels of land to implement carbon projects. They turned to Fused to simplify their data workflows.
Isaac Brodsky, the CTO of Fused, delved into the power of Fused during a LinkedIn live session with Matt Forrest. They discussed the contrast of Python vs. SQL for data analytics, the advantages of serverless geospatial processing, and showcased a live demo of the UDF Builder. During the demo, Isaac created a User Defined Function visualize Overture building footprints that are within a certain proximity of water.
TL;DR Fused extends DuckDB to bring quick serverless operations on any scale dataset. The result is a lightweight, portable, and flexible system that is simultaneously scalable, cost-efficient, and simple to integrate across the stack.
The combination of Fused serverless operations and DuckDB offers blazing fast data processing. Fused embraced Python to create serverless User Defined Functions (UDFs). Now, with the help of DuckDB, Fused enables developers to leverage the ease and familiarity of SQL in these functions - without compromising performance and parallelism.
Fused is a modern geospatial toolkit for companies to code, scale, and ship geospatial workflows of any size.
This week we are unveiling Fused, a toolkit to enable interoperability between all geospatial datasets and tools in the modern data stack. Fused is the glue layer that integrates data platforms with data tools via a managed serverless API.
Fused enables interoperability between datasets and tools in the modern data stack. It's a glue layer to integrate data platforms with data tools via a managed serverless API.