Green PRAXIS provides a digital platform that automates the collection and AI‑driven analysis of high‑resolution satellite imagery, land‑use, species, and regulatory data to deliver regulator‑grade environmental diagnostics at plot and portfolio scales. The solution generates biodiversity, carbon stock, and risk scores—along with mitigation recommendations and scenario modeling—enabling real‑estate managers, infrastructure operators, and urban planners to meet ESG reporting requirements and optimize land use efficiently.
Funding
$1.5M 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
Traditional environmental assessments are expensive, time‑consuming, and difficult to scale across large land portfolios, limiting operators’ ability to meet regulatory requirements and optimize land use.
Solution
Green PRAXIS offers a digital platform that automates the collection and analysis of high‑resolution satellite imagery, land‑use databases, species observations, and regulatory data. Its AI‑driven models generate regulator‑grade diagnostics on biodiversity, carbon stocks, and environmental risks (e.g., fire, flooding, heat islands) for thousands of hectares without field surveys. Users receive plot‑level scores, risk flags, and mitigation strategy recommendations, which can be iteratively re‑run on digital twins to compare management options. The platform delivers auditable, transparent reports that support CSRD, TNFD, due‑diligence, and portfolio‑management decisions, enabling faster, cost‑effective environmental planning at scale.
Target Audience
Primary customers are real‑estate portfolio managers, infrastructure operators (road, rail, energy), urban planners, and environmental engineering firms responsible for large land assets and seeking scalable ESG diagnostics.
Features
- Automated data ingestion from multispectral satellite imagery, land‑use and species observation datasets, and regulatory sources
- AI‑based scoring of biodiversity, carbon stock/sequestration, and environmental risk metrics at plot and portfolio levels
- TNFD‑compliant biodiversity analytics and carbon accounting for large‑scale asset portfolios
- Scenario modeling with digital twins to evaluate mitigation strategies and compare trade‑offs before field implementation
- Exportable, regulator‑grade reports with traceable data provenance for CSRD, TNFD, and permitting compliance
- Web‑based dashboard for interactive visualization, risk flagging, and action‑plan generation