GRAIL: AI translation for scientists application workflow on satellite data
The paper introduces GRAIL, an AI translation system designed to assist scientists in converting Python geospatial workflows into Spark-based programs. This system allows scientists to work with large-scale satellite data without needing to learn a new framework. GRAIL enhances existing libraries to make them compatible with large language models, improving the scalability and correctness of geospatial data analysis.
- ▪GRAIL translates Python scripts into executable Spark-based programs for satellite data analysis.
- ▪The system does not require scientists to learn a new framework, facilitating easier use.
- ▪GRAIL adapts existing libraries to be LLM-ready, improving the scalability of data workflows.
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Computer Science > Artificial Intelligence arXiv:2605.24784 (cs) [Submitted on 23 May 2026] Title:GRAIL: AI translation for scientists application workflow on satellite data Authors:Zhuocheng Shang, Ahmed Eldawy View a PDF of the paper titled GRAIL: AI translation for scientists application workflow on satellite data, by Zhuocheng Shang and 1 other authors View PDF HTML (experimental) Abstract:Domain scientists increasingly develop Python scripts to analyze satellite imagery but they lack scalability to large-scale data. This paper demonstrates GRAIL, an agentic translation system that converts Python geospatial workflows into executable Spark-based programs without requiring scientists to learn a new framework.
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