Dilepix develops a deep learning vision control system that utilizes computer vision and machine learning to automate tasks in precision agriculture, such as crop monitoring and livestock management. The platform enhances operational efficiency by enabling data-driven decision-making and simplifying quality control processes.
Funding
$1M 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
Precision agriculture tasks such as crop monitoring, livestock management, and quality control often require manual intervention, leading to inefficiencies and potential inaccuracies. Existing methods may lack the ability to process large volumes of complex and dynamic data, hindering data-driven decision-making.
Solution
Dilepix offers a deep learning vision control system that leverages computer vision and machine learning to automate tasks across precision agriculture. The platform provides tailored AI software solutions, including pre-trained models, and integrates directly into agricultural machinery for real-time data collection and automated actions. By processing images and video streams from onboard cameras, Dilepix's technology enables precise detection, localization, and interpretation of relevant events, facilitating autonomous operation and optimized resource allocation. The system's modular approach supports various applications, from autonomous piloting and guidance to precise object recognition and automated handling.
Target Audience
Dilepix primarily serves agricultural machinery manufacturers, robotics companies, veterinary groups, pharmaceutical companies, and innovative startups seeking to integrate advanced AI and vision capabilities into their products and services.
Features
- Custom AI software development for agricultural machinery, including robots, automated systems, and tractors
- Image analysis and computer vision technology for environmental perception and automated data collection
- Pre-trained AI models for rapid deployment and integration into existing systems
- Capabilities include autonomous piloting, automatic guidance, and precision object detection
- Solutions for livestock monitoring, including activity measurement, ovulation detection, and aggressive behavior detection in bovine and porcine animals
- Crop monitoring solutions for disease detection and yield prediction
- Cloud-based data analysis platform for processing large, complex, and dynamic datasets
- Support for various sensors and data acquisition methods, with recommendations for optimal sensor specifications