Miraterra utilizes advanced proximal sensing technology to deliver lab-grade soil analysis with real-time, parts-per-million accuracy, eliminating the need for traditional sample preparation. This approach addresses the critical issue of insufficient soil testing, enabling enhanced soil health monitoring and supporting carbon market credibility.
Funding
$6M 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
Current soil testing methods are often slow, expensive, and require extensive sample preparation, leading to infrequent testing and limiting the adoption of soil health initiatives. The lack of readily available, accurate soil data hinders effective soil management and carbon sequestration efforts. Only a small fraction of farmland is regularly tested, impeding progress in sustainable agriculture.
Solution
Miraterra offers a proximal sensing technology that delivers lab-grade soil analysis with real-time, parts-per-million accuracy, eliminating the need for traditional sample preparation. The system utilizes a combination of novel hardware, signal processing, machine learning, and computational chemistry to overcome the limitations of Raman spectroscopy. This approach provides accurate and adaptable measurements across diverse soil types, enabling enhanced soil health monitoring and supporting carbon market credibility. Miraterra's solution offers accurate, fast, and affordable soil measurement in soil labs, in the field, and in the ground.
Target Audience
Miraterra's primary customers include soil labs, agricultural businesses, and organizations involved in carbon sequestration and precision agriculture.
Features
- Proximal sensing technology for real-time soil analysis
- Lab-grade accuracy with parts-per-million resolution
- No sample preparation required
- Non-destructive, chemical-free testing
- Auto-focus and auto-calibration for simplified operation
- Software-defined hardware for upgradeable sensor abilities
- Machine learning models trained on millions of simulated tests and soil samples