IUNU builds an AI-driven platform (LUNA AI) for controlled environment agriculture, helping growers measure crop performance and optimize yield, labor, and quality. The tech stack—Python, PyTorch, Keras, React, PostgreSQL—reflects a machine-learning-first architecture focused on computer vision and predictive modeling. Active projects in robotic systems and distributed data processing, paired with hiring concentrated in engineering (mostly senior-level), suggest the company is scaling toward autonomous greenhouse operations rather than just analytics.
IUNU is a Seattle-based AI software company serving the controlled environment agriculture (CEA) industry. The LUNA AI platform functions as a greenhouse operating system, combining computer vision, machine learning, and workflow automation to help growers measure crop performance, interpret data, and act on insights in real time. The company targets mid-market and enterprise growers struggling with yield forecasting, manufacturing timeliness, waste reduction, and cost control. With 51–200 employees and engineering-heavy hiring, IUNU is actively developing robotic integration and distributed data infrastructure to support larger-scale deployments.
LUNA AI is an operating system for greenhouse profitability that uses computer vision and machine learning to measure crop performance, interpret data, and optimize yield, labor, and quality for controlled environment agriculture growers.
IUNU's core stack includes Python, PyTorch, Keras, and scikit-learn for ML; React and Next.js for frontend; PostgreSQL and SQL for data; Node.js and Java for backend services; and SolidWorks for hardware design.
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