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Robovision.ai
Robovision.ai

Robovision.ai

Low Code/No Code

Robovision.ai
Robovision: A Platform for Dynamic Vision AI Computer vision is the field of artificial intelligence that enables machines to see and understand the world. It has many applications across different industries, such as agriculture, manufacturing, healthcare and retail. However, developing and deploying computer vision solutions can be challenging, especially in dynamic environments where the data and the requirements change frequently.
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That's why Robovision, a computer vision company based in Belgium, has created a powerful and easy-to-use platform that helps companies automate and enhance their business operations through smart computer vision applications that scale. Robovision AI (RVAI) is a central platform that allows users to manage vision intelligence inside smart machines, without the need for AI experts.

RVAI enables users to create, train, deploy and monitor computer vision models for various use cases, such as quality control, object detection, segmentation and classification. Users can also leverage 3D deep learning, which is a cutting-edge technology that can handle complex and volumetric data. RVAI supports both 2D and 3D data formats, such as images, videos, point clouds and meshes.

One of the key features of RVAI is its user-friendly interface that allows users to interact with their data and models in a visual way. Users can label their data, annotate their images, adjust their parameters and see their results in real time. They can also collaborate with other users and share their projects and insights.

Another key feature of RVAI is its edge computing capabilities. Robovision Edge is a device that enables real-time, on-premises automation solutions powered by vision AI. It can capture, process, store and upload new images to the right models in the RVAI platform. Robovision Edge ensures maximum security and zero production delay for latency-critical applications.

Robovision has been trusted by market leaders as the #1 platform for dynamic 2D and 3D vision AI. Some of their success stories include:

- Integrating computer vision into horticulture robots that can recognise, pick and pot plant cuttings.
- Improving CT-scan diagnosis with AI algorithms that can detect lung nodules and other abnormalities.
- Automating defect detection for various products, such as breads, semiconductors and metal parts.

Robovision believes that the future of AI is where humans and machines collaborate intelligently. Their mission is to make computer vision more accessible and scalable for everyone. If you are interested in learning more about Robovision and how they can help you with your vision AI needs, you can visit their website at https://robovision.ai/ or request a demo.

Pros
  •  Robovision AI is a central platform to manage vision intelligence inside smart machines, without the need for AI experts.
  •  Robovision AI supports dynamic environments and enables AI adaptation and expansion without coding.
  •  Robovision AI integrates all technologies in one toolkit and simple interface, allowing data scientists to focus on building solid models and solving business problems.
  •  Robovision AI facilitates collaboration and reuse of computer vision algorithms among different users and projects.
  •  Robovision AI can run on any infrastructure and has no vendor lock-in.

 

Cons
  •  Robovision AI may not be suitable for applications that require customised or specialised computer vision solutions that are not supported by the platform.
  •  Robovision AI may have a learning curve for users who are not familiar with the platform's interface and workflow.
  •  Robovision AI may have limitations in terms of scalability, performance, security or reliability depending on the infrastructure and deployment options chosen by the users.
  •  Robovision AI may have compatibility issues with some existing software or hardware systems that are not compatible with the platform's SDK or API.
  •  Robovision AI may have ethical or legal implications depending on the type and use of data and models involved in the computer vision projects.

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