Matrice.ai and Voltage Park join forces to make no-code computer vision faster and more accessible for businesses

Matrice.ai partners with Voltage Park to accelerate no-code computer vision AI, cutting development time by 40% and costs by 80%. Their platform supports deployment across cloud, on-premises, and edge devices.

Categorized in: AI News IT and Development
Published on: Jul 30, 2025
Matrice.ai and Voltage Park join forces to make no-code computer vision faster and more accessible for businesses

Matrice.ai Partners with Voltage Park to Speed Up No-Code Computer Vision Development

Computer vision startup Matrice.ai Inc. has expanded its seed funding round, now led by cloud infrastructure provider Voltage Park Inc. Other investors include Ax3.ai, Plug and Play Ventures, and several angel investors. While the exact amount raised remains undisclosed, the partnership signals a strategic push to accelerate no-code AI development.

Simplifying Computer Vision with No-Code

Matrice.ai offers a no-code platform that allows users to create AI models capable of interpreting their environment without needing to write code. This approach reportedly speeds up development and deployment by up to 40% and can reduce costs by as much as 80%, by eliminating much of the manual coding effort.

The platform is designed for users regardless of their programming skills. It provides an intuitive interface where ideas for computer vision models can be outlined, then automatically generates the necessary code and initiates training. Matrice.ai emphasizes a data-centric model design, offering automated tools for dataset labeling to improve model accuracy.

Once training meets user requirements, models can be deployed across various environments including cloud, on-premises, or edge devices, offering flexibility for different operational needs.

Applications and Impact of Computer Vision

Computer vision enables machines to quickly interpret visual data, which enhances automation across industries. For example:

  • Manufacturing uses computer vision for rapid defect detection in products or components, improving quality control.
  • Healthcare benefits from faster analysis of medical scans, assisting in diagnoses.
  • Retail leverages it for virtual try-ons, enhancing customer experience.
  • Automotive industries apply it to help self-driving cars detect and avoid obstacles.

Matrice.ai's Growing Presence

The company’s Vision Factory platform is already powering hundreds of live cameras globally, including in the Philippines and the Middle East. Customers span energy, retail, and public sectors, with applications in oil fields, smart cities, stadiums, and more.

Voltage Park: More Than an Investor

Voltage Park brings more than funding to the table. It offers a cloud infrastructure platform with over 24,000 GPUs across six data centers, providing on-demand, bare-metal GPU access without virtualization layers. This setup enhances performance and predictability for AI training and inference workloads.

Matrice.ai’s CEO Amar Krishna highlights this partnership as key to building and deploying highly accurate, custom vision models faster and at lower costs than before. Voltage Park’s Chief Product and Technology Officer Saurabh Giri notes the startup’s practical expertise in vision AI that turns raw data into actionable intelligence across industries.

Looking Ahead

Matrice.ai plans to expand beyond Asia and the Middle East into the U.S. and Europe. The company is also exploring new use cases such as flare detection, crowd analytics, and queue monitoring to broaden the scope of its computer vision applications.

For IT professionals and developers interested in no-code AI workflows and computer vision, Matrice.ai’s approach offers a practical way to accelerate project timelines while reducing costs. Their collaboration with Voltage Park provides the infrastructure backbone to support larger-scale deployments and complex AI workloads.

Learn more about AI development and computer vision training with resources available at Complete AI Training.


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