Monarcha provides an AI‑driven platform that automatically extracts and georeferences land descriptions, coordinates, and vector geometries from scanned or digital maps, plats, deeds, and field notes. The system detects projection, converts data to GIS formats (GeoJSON, Shapefile, WFS) with sub‑meter accuracy, and delivers results via a cloud repository, web dashboard, and API for integration into existing GIS workflows.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Mining and civil‑engineering teams spend weeks manually georeferencing legacy maps, plats, deeds, and field notes, a process that requires specialized GIS expertise, is prone to projection errors, and delays data‑driven decision making.
Solution
Monarcha delivers an AI‑driven geospatial platform that automatically extracts land descriptions, coordinates, and vector geometries from scanned or digital documents. Its vision‑AI engine parses text, symbols, and raster imagery, aligns them to the correct coordinate system, and outputs a ready‑to‑use GIS layer in under two minutes. The service supports any document format—PDFs, TIFFs, JPEGs—and handles historic datums as well as modern projections, achieving sub‑meter accuracy without manual digitization. Processed datasets are stored in a cloud repository and can be queried via a web dashboard or API, enabling natural‑language searches and seamless integration with existing GIS workflows. This automation frees engineers to focus on analysis and field work rather than data entry.
Target Audience
Primary customers are mining companies, exploration geologists, and civil‑engineering firms that need to digitize legacy survey data and integrate it into modern GIS environments. Secondary users include land‑surveyors, GIS analysts, and government agencies managing cadastral records.
Features
- Vision‑AI pipeline that combines OCR, symbol detection, and raster‑to‑vector conversion to generate georeferenced vector data from maps, plats, deeds, and field logs.
- Automatic projection detection and transformation, supporting historic datums (e.g., NAD27/83) and custom mine grid systems with sub‑meter positional accuracy.
- Universal document ingestion handling PDFs, scanned images, and CAD exports, with batch processing capability for large archives.
- Structured GIS output delivered as GeoJSON, Shapefile, or WFS services, ready for consumption in ArcGIS, QGIS, or proprietary platforms.
- Cloud‑native analytics engine that indexes extracted attributes for natural‑language querying and fast spatial searches.
- RESTful API and SDKs for programmatic access, enabling integration into existing data pipelines and enterprise GIS portals.
- Enterprise‑grade security with end‑to‑end encryption, role‑based access controls, and compliance with industry data‑privacy standards.