LGND provides a platform for creating and managing geographic embeddings, enabling developers and analysts to build location-aware applications. Their services simplify the process of integrating spatial data into machine learning models, allowing businesses to leverage location intelligence for various use cases.
Funding
Funding not disclosed
Founders
Product
Problem
Analyzing Earth observation data, such as satellite imagery, to derive actionable insights is traditionally complex, expensive, and requires specialized expertise. Existing solutions often involve extensive coding, manual data processing, and significant computational resources, hindering widespread adoption and timely decision-making.
Solution
LGND provides a platform that simplifies the creation, tuning, storage, and serving of geographic embeddings, enabling developers and analysts to build location-aware applications with ease. By leveraging large AI models, LGND transforms Earth data into a powerful new data object, making it faster and more affordable to generate insights. The platform offers a suite of integrated services and tools that eliminate the need for extensive coding, allowing users to generate collections of geographic embeddings, refine and customize them, and leverage them to identify similar features or locations globally. LGND's goal is to make Earth data universally accessible and actionable through AI, empowering businesses to innovate, solve real-world challenges, and drive meaningful impact.
Target Audience
LGND targets developers and analysts across various industries, including government, defense, insurance, finance, agriculture, supply chain, climate tech, and real estate, who seek to leverage location intelligence for diverse use cases.
Features
- Code-free generation of geographic embedding collections based on area, model, time range, and image source
- Tools to analyze spatial data, visualize layers, label features, and filter results
- Automated summarization of findings and access to detailed metadata
- Organized storage and management of collections with essential metadata
- Flexible endpoints to leverage collections for identifying similar features or locations globally
- Configurable analysis workflows and adjustable model parameters
- Seamless collaboration through exporting findings and generating public links
- Hosted vector search database to store and index spatiotemporal embeddings across space, time, and zoom levels
- Model warehouse to generate, fine-tune, and serve embeddings from top AI models
- Integrated data sources for streamlined Earth data analysis
- Developer tools (SDKs and APIs) to incorporate geographic embeddings into applications