The mint-1 project, also known as SATQUERY X, is a high-tech satellite image analysis and AI dashboard designed for ISRO and advanced users. It leverages cutting-edge technology and AI models to provide comprehensive satellite imagery analysis. The system is built using a React/Next.js frontend and a FastAPI backend, with a focus on providing a cinematic and futuristic user experience.
The SATQUERY X system is designed to facilitate satellite image analysis through a user-friendly dashboard. It supports image uploads, GeoTIFF metadata validation, and advanced AI-driven analysis. The system includes a Planner Agent for task routing and a GeoReason Engine for cross-verifying analysis outputs. Users can generate detailed PDF reports of their analyses. The system is built with a focus on high-tech design and user experience, using a specified tech stack and adhering to a 24-hour execution plan.
The system is delivered as a web application with a React/Next.js frontend and a FastAPI backend. It requires user authentication for accessing protected features such as image uploads and analysis dashboards. The system persists data using PostgreSQL/PostGIS and generates reports using ReportLab. The Planner Agent and GeoReason Engine are key components, with the former handling task routing and the latter providing verification and confidence scoring. The system's design is inspired by Gleb Kuznetsov's cinematic future tech style, emphasizing a high-tech and immersive user experience.
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As an Analyst, I should be able to upload satellite images for analysis.
As an Analyst, I should be able to view analysis results on a dashboard.
As an Analyst, I should be able to generate and download a PDF report of my analysis.
As an Analyst, I should be able to log in to access my projects and analyses.
A full-bleed 3D scene dominates the viewport on the Home page, with floating glass panels displaying live data streams over a dark void. Electric cyan and magenta glows highlight important sections, creating an immersive and futuristic experience.

Four verified pipelines carry every query from raw imagery to a cross-checked, explainable answer.
Upload optical and SAR imagery for automated interpretation. VQA and grounding models identify rivers, buildings, forests, and water bodies directly from the frame.
01The Planner Agent routes each query to specialist models — change detection, grounding, and optical-SAR fusion — assembling explainable answers from real model output.
02Rasterio and GDAL read every upload for CRS, resolution, and sensor type before analysis begins, surfacing validation status ahead of processing.
03ReportLab compiles the query, imagery, highlighted map, statistics, and confidence score into a complete downloadable report for offline review.
04Sign in to route queries through the Planner Agent, cross-verify optical and SAR imagery, and get an explainable confidence score in minutes.

Four verified pipelines carry every query from raw imagery to a cross-checked, explainable answer.
Upload optical and SAR imagery for automated interpretation. VQA and grounding models identify rivers, buildings, forests, and water bodies directly from the frame.
01The Planner Agent routes each query to specialist models — change detection, grounding, and optical-SAR fusion — assembling explainable answers from real model output.
02Rasterio and GDAL read every upload for CRS, resolution, and sensor type before analysis begins, surfacing validation status ahead of processing.
03ReportLab compiles the query, imagery, highlighted map, statistics, and confidence score into a complete downloadable report for offline review.
04Sign in to route queries through the Planner Agent, cross-verify optical and SAR imagery, and get an explainable confidence score in minutes.
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