Lightscline’s AI reduces 90% of AI infra and human time & costs by learning to predict using just 10% data.


Our AI uses 4 lines of code to redefine the 1940s Nyquist theorem for scientific computing

                from lightscline.lightscline import LightsclineEdge
                ## Load data into Lightscline
                ls = Lightscline(data=data,fs = SAMPLING_FREQUENCY)
                ## Reduce the amount of data by 90% of the original
                ## Train the model
                ls.train_model(verbose=True,n_iters = 1000)
                ## checking the results

Reduce your data infrastructure and human capital costs by 10x. With our software, you can achieve:

  • > 10x faster for same analytics accuracies
  • 90% reduction in data infra costs
  • 10x productivity increase (data science/ML teams)- More model deployments
  • >10x reduction in edge computing power than conventional approaches
  • Automatically selects the 10% important windows

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