Mowito was founded in 2021 and has made significant moves in the robotic arms segment since then. So, can you share some information with our TechiExpert readers about what inspired the founding of the startup and what gap are you addressing in automation?
Adityanag and I have been working in the warehouse and factory automation space since 2019, visiting over 50 factories and warehouses to analyze their automation challenges. We recognized that robotic automation is essential for process efficiency. While the hardware for robotics has matured, many companies still lack intelligent software to effectively utilize these robots for automation.
Mowito was founded in 2021, and we focused on solving the challenge of robotic picking. Although major robotic arm manufacturers control 75% of the market with well-developed offerings, they fall short in providing intelligent software capable of guiding robotic arms to pick items as humans do—particularly when handling previously unseen items without causing damage.
Picking is a fundamental process in both warehouses and factories; every online order involves a product being picked from storage and packaged. However, the variation in shapes, sizes, and movement often prevents typical robotic arms from performing these tasks effectively. To address this, we developed vision-based AI software that analyzes scenes captured by cameras to guide robotic arms in picking a wide variety of items and placing them in designated locations.
How do you adapt your software to handle varied products across industries like automotive, FMCG and pharmaceuticals?
Our software is powered by AI, enabling it to learn and adapt autonomously. We have trained it on a variety of products, including fruits, vegetables, FMCG, CPG, electronics, and pharmaceuticals. It can detect both familiar and new objects in its environment. Once an object is detected, it determines its orientation, the best gripping method, and the right pressure to apply, ensuring delicate items like tomatoes aren’t damaged. In cases where detection fails, the software alerts a remote human operator, who helps identify the object, allowing the software to learn from this interaction and improve its detection capabilities for future instances.
You may have received feedback from deployments with companies like Denso. Can you share this with our TechiExpert readers?
Ans: Mowito-powered robots work on automotive components on a conveyor-based assembly line, handling up to 12 units per minute and 720 units an hour. This high throughput highlights the efficiency of our technology in fast-paced environments. In another deployment, a single Mowito-powered ‘Mobile’ robotic arm can tend to up to 6 machines. Earlier, a single robotic arm could tend to a maximum of 2 machines. This has resulted in a 3x boost in productivity, showcasing the flexibility and effectiveness of our AI-driven solution.
Denso is highly satisfied with the outcomes and is now requesting additional deployments, which further confirms our technology’s effectiveness in enhancing operational efficiency for demanding industrial tasks.
What challenges do you face in scaling globally and what are the approaches being implemented to reach international markets?
We understand the significance of building a strong foundation to attract international clients being a startup with a small team. Two key factors are crucial: having a robust portfolio of existing customers and ensuring our clients have confidence in our post-sales support capabilities.
We strategically target applications that are particularly challenging to automate, such as assembling objects on a moving conveyor. Customers are eager to find effective solutions for these complex applications and are open to working with startups like ours to address their needs.
Furthermore, we have partnered with multiple system integrators in the U.S. who provide automation solutions to notable companies like Tesla, Lucid Motors, and Caterpillar. These system integrators recognize our technology as innovative and want to use it to automate processes, which are considered hard to automate.
What role do you see Mowito playing in the future of manufacturing and warehouse automation?
Mowito is revolutionizing factory and warehouse automation by developing advanced software that enhances the capabilities of robotic arms. While traditional robots have been limited to specific, isolated tasks, Mowito’s solution enables robots to work alongside humans, performing a variety of tasks with greater efficiency. Our software minimizes the need for extensive infrastructure and reduces the time required to configure robots for different tasks. Additionally, it makes robotic arms adaptable to changes in their environment, such as object location, shape, and size, allowing them to operate as robustly as human workers, but with higher precision and flexibility.
What new features or advancements is Mowito planning to enhance robotic efficiency further?
Mowito is working on developing AI models that enable robotic arms to learn tasks through demonstrations performed by humans. For instance, if a robot needs to learn how to fold and pack a shirt, it can acquire this skill by watching a video of a human completing the same task. This approach reduces the time required to configure the robot and expands the range of applications that can be automated by robotic systems.
Mowito is working on advancing mobile robotic arms, which are capable of moving on wheels or legs. This mobility significantly expands the range of tasks that a single robotic arm can handle. The company has successfully deployed mobile robotic arms and is receiving multiple requests for more deployments. Currently, these robotic arms are being used for machine tending, and Mowito is working on developing applications for sortation in warehouses and automating processes inside chemical labs.
