Unlocking the future of logistics demands a visionary approach that empowers robotic solutions. Meet Fizyr, a collective of Computer Vision pioneers, armed with expertise in collaborating with robotics and system integration leaders within the supply chain space.
Our Fizyr Computer Vision software seamlessly integrates with essential automation components from top-tier suppliers – encompassing everything from robots and precision cameras to agile grippers and beyond. Through these partnerships, we’ve played an instrumental role in the world of automation. Join us on this transformative journey as we redefine the landscape of what’s possible in logistics.
Based on experience (gathered data) and experimentation (deep learning and advanced heuristics development), Fizyr’s software will denote the best grasping tactic. The gripper’s capabilities are put to use optimally, taking into account the always changing scene.
Effortlessly streamline the depalletizing process, ensuring efficient and precise handling of goods.
Experience unparalleled precision and efficiency in selecting and placing items, transforming your workflow.
Seamlessly unload cargo from trucks, trailers, and containers with unmatched efficiency and accuracy.
Elevate your parcel sorting operations with our advanced Computer Vision software, enhancing throughput and reducing errors.
We are at the forefront of innovation, continually staying up to date with the latest advancements in neural network models and the ever-evolving landscape of AI and machine learning.
Fizyr’s expertise is deeply rooted in logistics. We work closely with an experienced commercial team and strategic partners, ensuring a comprehensive understanding of the logistics challenges that Computer Vision is poised to solve.
Our solution partners engage in a collaboration with Fizyr professional services and partner project teams. Together, we solve how computer vision serves as a pivotal element within robotic cells across a diverse range of applications.
Fizyr boasts steadfast technical relationships with leading robotic manufacturers, camera vendors, and gripper suppliers. This ensures a seamless interoperability between our Computer Vision and other integral components of robotic cells.
When it comes to logistics automation, success is dependent on three critical pillars:
Robotics: The hardware that brings movement to the operation.
Vision: Vision captures the essence of intelligence, equipping robots with the knowledge of what they're handling, how to handle it, and more.
Tools: Grippers, conveyors, controllers, and other pivotal components complete the package, seamlessly connecting the dots in the workflow.
Computer Vision has emerged as a linchpin in the realm of supply chain automation, responsible for data capture and the intricate decision-making that underpins the efficient management of packaged goods.
At Fizyr, we’ve curated a versatile toolkit that seamlessly integrates with leading robotic and camera hardware, while also managing complex gripper commands. Our Computer Vision is engineered to perform precise package segmentation across all categories, decipher grasp poses, prioritize tasks, and expertly manage challenges such as occlusion and multi-pick scenarios.
Unlike off-the-shelf Computer Vision solutions, our software is purpose-built to create a neural network learning environment tailored specifically for optimizing the accuracy and efficiency of logistics workflows; we understand that ‘one size fits all’ doesn’t suffice in the complex world of logistics.
Our Partner Program centers around two pillars:
Shared Business Goals: Our primary mission is to empower and facilitate the development of products that redefine excellence within the logistics automation space. Together, we’ll forge robust solutions that resonate with the industry.
Strategic Business Development: Collaboration is at the forefront of everything we do. Leveraging our extensive network within the realms of robotics, warehouse automation, and the logistics industry, we navigate opportunities for mutual growth.