Tools to simplify the process of building Deep Learning Systems


Work bench for Deep Learning

VEGA is designed for researchers and data scientists to build and deploy Deep Learning algorithms at scale. An end to end platform, 'VEGA' simplifies complex ‘AI’ processes enabling developers and enterprises to focus on core product features.

Build complex neural nets

Create complex architectures in Braid through coding or by using drag and drop features, in a snap!

  • Simple definition of architectures
  • Highly modular
  • Easy to synthesize and visualize

Braid is super flexible and modular library designed for speed and ease.

Drag and Drop layers to create sophisticated architectures that are ready for training and deployment.

Plug in data and train networks

'VEGA' is Integrable with multiple Data platforms. Given a source of training data, the work bench can access and learn from it. Vega can ingest live data and learn continually through feedback loops at defined frequency.

Deploy and Scale seamlessly

Vega provides a single click option to deploy on Arya's cloud. Or you could deploy to your data centers via provisioning layer. Through Vega, continue monitoring your application and scale as required. Vega's hardware recommendations include optimal combinations of CPUs and GPUs.

Deep Learning - One Workbench, Many Use Cases

Computer Vision Diagnostics or IoT or Analytics or Robotics?

Vega works for many Deep Learning use cases.





Everything an enterprise needs in the platform!


Rapidly build, train and reconfigure neural networks for faster time-to-deploy


Monitor deployments and performance. Use metrics to make decisions on scale and architecture.


Cloud or private data centers – deploy and build complex solutions as per needs.


The workbench allows collaborative modelling among multiple team members.


An advanced dashboard allows enterprises to monitor all WIP development activities and deployments through a single interface.


Data sets that are structured or unstructured or hybrid? VEGA works with any data sets!

Are you an enterprise?

Want to discuss more about the platform and deployment?

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