LIGHTSCLINE

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
                ls.reduce_and_preprocess_data(per_reduction=90)
                ## Train the model
                ls.train_model(verbose=True,n_iters = 1000)
                ## checking the results
                ls.test_model()

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

Backed by:

LIGHTSCLINE

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