CTO
Jaipur Robotics
Jaipur Robotics provides computer vision and deep learning solutions for waste-to-energy plants, helping operators detect hazardous waste, map calorific values, and optimize crane movements. Their technology reduces unplanned shutdowns by 10% and saves plants up to €9 million annually through improved waste mixing. The system requires no calibration and works in bunkers of any size.
- Artificial Intelligence
- Data & Analytics
- Clean Technology
- Energy
- Industrial Automation
- Software Only
- Wellness & Fitness Technology
Updated 1 month ago
Funding
Raised to date
€5.2MRaised 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.
Est. $5.7Macross 3 rounds
EVHTTS€4.3M · Seed
Announced Sep 2026 · from article date
Disclosed cumulative: $5.7M
3/3
RoundDateAmountValuationInvestors
Founders
Product
Problem
Waste-to-energy plants lose up to $4.3 million per plant annually due to manual and inefficient waste handling. Inefficient mixing, undetected hazardous items, and unoptimized crane operations lead to equipment damage, unplanned shutdowns, and reduced energy output.
Solution
Jaipur Robotics designs advanced computer vision algorithms tailored to the waste-to-energy sector that improve plant efficiency, reduce emissions, and minimize unplanned shutdowns. Their Jaipur Intelligence platform uses patent-pending deep learning technology to identify hazardous or problematic waste items directly in bunkers and at truck unloading bays, preventing operational disruptions. The solution provides real-time calorific value mapping (Lower Heating Value) throughout the entire bunker volume, guiding crane operators to mix waste effectively before combustion. Crane tracking capabilities offer precise monitoring and prediction of crane positions and operational status, enabling optimized trajectory planning and reduced downtime. The system requires no initial calibration, works in bunkers of any size, and delivers near-zero false positives from day one.
Target Audience
Primary customers are waste-to-energy plant operators and management teams seeking to improve operational efficiency, reduce costs, and minimize unplanned shutdowns through AI-driven waste recognition and automation.
Features
- Computer vision-based detection of oversized and dangerous items in bunkers and unloading bays with intuitive reporting for proactive management
- Real-time calorific value mapping (LHV) using deep learning algorithms that detect waste characteristics even below the surface
- Crane tracking with real-time monitoring and prediction of position and operational status for one or multiple overhead cranes
- No initial calibration required and compatible with bunkers of any size
- Near-zero false positives from day one with detailed historical reporting and analytics for continuous improvement
- Seamless integration with existing plant operations requiring minimal setup