The startup develops business intelligence services that utilize synthetic aperture radar technology to analyze satellite data. It provides infrastructure that enables companies and research institutions to efficiently access and interpret satellite data, addressing the challenges of satellite utilization in various applications.
Funding
Funding not disclosed
Founders
Product
Problem
Decision-makers in various industries often rely on lagging indicators like news and government statistics, which can lead to delayed reactions and missed opportunities. Obtaining timely and accurate information, especially in areas with limited access or transparency, remains a significant challenge.
Solution
Stellarvision provides business intelligence services using synthetic aperture radar (SAR) and other satellite imagery to deliver timely, accurate, and objective data for informed decision-making. The company's machine learning and GIS analytics transform raw satellite data into actionable insights, offering a solution to information asymmetry. Stellarvision's services include monitoring crop yields, supporting smart farm initiatives, predicting flood damage, and analyzing port shipping traffic. By leveraging satellite technology, Stellarvision overcomes traditional barriers to data collection, providing valuable information even in remote or inaccessible locations. The platform helps users to anticipate market trends, optimize resource allocation, and mitigate risks associated with environmental changes and logistical bottlenecks.
Target Audience
Stellarvision serves organizations across agriculture, logistics, disaster management, and investment sectors that require timely geospatial intelligence for strategic decision-making.
Features
- Crop yield monitoring using satellite imagery, vegetation indices, weather data, and GIS data to predict harvests and inform market forecasts.
- Smart farm solutions providing insights into cultivated area, crop health, and yield analysis using satellite imagery optimized for small-scale, diverse-crop farming.
- Flood damage assessment generating flood extent maps using satellite imagery and geographic information, calculating impact on affected farmland and populations.
- Port shipping traffic analysis quantifying vessel traffic and flow using satellite imagery and AIS data to assess port logistics and potential supply chain disruptions.
- Utilizes machine learning and deep learning for advanced GIS analysis and data processing.