Satellite-powered water infrastructure risk detection using AI
Tenchijin applies satellite imagery and machine-learning models to predict failures in water systems before they surface — a focus reflected in their active work on risk-detection and anomaly-detection AI models. The stack is frontend-heavy (Vue, React, TypeScript) paired with geospatial tooling (GIS, Plotly), suggesting a product centered on visualization of satellite-derived insights. Hiring is concentrated in engineering and product roles, nearly all senior or mid-level, indicating a transition from validation toward scaled feature development.
Tenchijin is a Tokyo-based space-tech company founded in 2019 by former JAXA (Japan Aerospace Exploration Agency) professionals and agricultural IoT experts. The core offering is the COMPASS platform, which ingests satellite data and AI to surface actionable intelligence for water management, renewable energy, agriculture, and emissions monitoring. The flagship product, KnoWaterleak, targets water infrastructure operators with predictive leak detection, reducing inspection costs and labor time significantly. The company operates in Japan and serves government and utility-sector customers.
Frontend: Vue, React, TypeScript, JavaScript, HTML, CSS. Backend/data: AWS, GIS, matplotlib, Seaborn, Plotly. Version control: GitHub. Design: Figma.
Active projects include risk-detection and anomaly-detection AI models, feature additions to the COMPASS platform, a renewable-energy variant, web-GIS application development, and core service expansion.
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