LGND provides an AI‑driven Earth intelligence platform that converts satellite imagery into searchable vector embeddings, enabling fast similarity search, semantic queries, and change detection without custom ML models. Through APIs, SDKs, and no‑code apps like LGND Studio and Discover, analysts and developers can generate, explore, and export geospatial insights at scale.
Funding
Funding not disclosed
Founders
Product
Problem
Analyzing satellite imagery at scale requires specialized expertise, heavy computational resources, and complex workflows, making it difficult for analysts, developers, and organizations to quickly extract actionable insights from Earth observation data.
Solution
LGND delivers an AI‑driven Earth intelligence platform that transforms raw satellite imagery into searchable vector embeddings. Users can generate embeddings for any geographic area and time range via the LGND API, then perform fast similarity search, semantic text‑based queries, and change detection without building custom machine‑learning models. No‑code applications such as LGND Studio and LGND Discover let analysts and non‑technical teams create, validate, and explore geospatial datasets through guided workflows and conversational interfaces. The platform scales from small pilots to enterprise deployments, offering SDKs, APIs, and managed vector indexes that integrate seamlessly into existing pipelines and GIS tools.
Target Audience
Primary customers are geospatial analysts, data scientists, and product teams that need rapid, AI‑enhanced insight from satellite imagery, as well as developers building Earth‑observation features into applications.
Features
- API and SDK for generating geo‑embeddings from open‑source and commercial satellite imagery, with customizable chip sizes and temporal filters
- Vector indexing and similarity search that supports both visual chip‑based matches and natural‑language queries (e.g., “solar farms in California”)
- Change detection endpoint that highlights semantic or visual differences between historical and current imagery, with scoring and ranking
- No‑code collaborative apps (LGND Studio, LGND Discover) for dataset creation, annotation, validation, and conversational map search
- Export of results in common geospatial formats (CSV, GeoJSON, Shapefile, KML, image tiles) for downstream analytics
- Scalable credit‑based pricing that charges only for embedding generation; all search, indexing, and storage are included at no extra cost