Platform Overview

The Skymind platform guides engineers through the entire workflow of building and deploying ML models for enterprise applications on JVM infrastructure.

Engagement Path

now
Today

AI-Readiness Evaluation

Discuss use case, available data, and desired outcome.

1 Day

Discovery Meeting

Deep dive into business requirements and deployment scenarios.

1 Week

1-Month Free Trial

Skymind engineer to guide installation, setup, and configuration.

1 Month

Deploy AI Into Application

Scale Out

Command Line Interface

Seamlessly swap models from sandbox into production in a couple lines of code.

                import skil_client
                uploads = client.upload("tensorflow_rnn.pb")
                new_model = DeployModel(name="recommender_rnn", scale=30, file_location=uploads[0].path)
                model = client.deploy_model(deployment_id, new_model)
                ndarray = INDArray(array=base64.b64encode(x_in))
                input = Prediction(id=1234, prediction=ndarray, needsPreProcessing=false)
                result = client.predict(input, "production", "recommender_rnn")
              

Supported Tools

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Big Data Connectors

Application Frameworks

Model Import

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