Edge Forestry
Edge Forestry provides an AI-driven platform that converts photos of trees into accurate disease diagnoses within seconds. Landowners and managers upload images or share a public Google Drive folder, select the suspected disease, and instantly receive probability scores with mapped visualizations across their property. The platform currently supports Hemlock Woolly Adelgid and Oak Wilt detection with 90%+ reported model accuracy.
- Artificial Intelligence
- Software Only
- Data & Analytics
- Agriculture Technology
Funding
Founders
Founder details are not available yet.
Product
Problem
Forest health management currently relies on manual inspection and expert assessment, which is time-consuming, costly, and difficult to scale across large land areas. Early detection of diseases like Hemlock Woolly Adelgid and Oak Wilt is often missed until significant damage has occurred, leading to wider spread and higher remediation costs.
Solution
Edge Forestry provides an AI-driven platform that converts photos of trees into accurate disease diagnoses within seconds. Landowners and managers upload images or share a public Google Drive folder, select the suspected disease, and instantly receive probability scores with mapped visualizations across their property. The platform uses machine-learning models trained on specific forest pathogens to deliver highly accurate predictions, enabling proactive management decisions. Users can filter results by classification and export findings in CSV or GeoJSON formats, allowing seamless integration into existing land-management workflows. The system also maintains a persistent dashboard of past diagnoses for easy reference and trend tracking.
Target Audience
Primary customers are forest landowners, land managers, arborists, and conservation organizations responsible for maintaining large or ecologically sensitive forested areas.
Features
- Photo-based AI diagnostics with disease-specific probability scoring for Hemlock Woolly Adelgid and Oak Wilt, with 90%+ reported model accuracy
- Mapping integration that visualizes disease presence and spread across user-defined land areas
- Batch processing capability through labeled entries and public Google Drive folder sharing
- CSV and GeoJSON export options with filtering by classification for downstream analysis
- Persistent dashboard that stores previous diagnosis results for instant retrieval and comparison