• Why hAIsten

    Speeds up your model training and reduces time to production

    Challenges of deep learning

    • Model training: Waiting for computing takes most of your time, and 80% of data scientists experience the same challenges as you. You will have more opportunities to test different algorithms and get better predictions if the computing time can be shortened.
       
    • Model deployment: It is usual to have another 12 to 24 months of work before the model can be deployed and get into production.

    With AI software: speed and agility

    You are able to

    • speed up your model training speed by 7x, saving 90% of the time for computing, and build your model within 1-2 months.
    • deploy your model with a low-code platform, with our built-in toolkits for better model inference.

  • How hAIsten Model Training Works

    Train your model in distribution

    1

    Creat project

    An infrastructure-optimized environment is ready for you

    2

    Connect to dataset

    Select your datasets

    3

    Upload your model

    Upload your models based on Pytorch, Tensorflow or TensorRT

    4

    Pay as you go

    Start to train your model in 7x speed on multi-GPUs

  • How hAIsten Inference Works

    Deploy your model within one-command

    1

    Select model 

    Select a model that you have trained and vaildated

    2

    Assign model to cloud or edge devices

    Connect to your edge devices or cloud platforms

    3

    Run

    Get your model prediction results

  • Case Studies

    Faster AI development. More real-time insights.

    AI in construction

    Safer working enviroment for workers with AI software

     

    AI in healthcare

    Better medical monitoring for saving lives with AI software

     

    AI in manufactorcing

    Larger scale deployment for defect detection and predictive maintenance

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