Skymind Intelligence Layer

A Platform for Operating Models in Production

Overview

The Skymind Intelligence Layer (SKIL) is a software distribution designed to help enterprise IT teams manage, deploy, and retrain machine learning models at scale. By treating distributed systems as first class citizens, SKIL streamlines the path from research to production.

Why SKIL?

Data Scientists

Interoperability with widely used data science libraries.

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Executives

SKIL helps innovation teams accelerate time to value.

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Architects

Designed to be embeddable within IT environments.

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DevOps/SRE

Scalable, distributed, fault-tolerant machine learning.

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Unified AI Infrastructure

SKIL enables interoperability between data science and big data frameworks by standardizing and orchestrating AI workflows within a single, consolidated platform.

Command Line Interface

Set up internal services and manage data science workflows from the command line.

          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")
        

Features

Feature Description Community Enterprise
Interoperability
Deeplearning4j Deep Learning for the JVM on Hadoop & Spark
Tensorflow Protobuf Import Pre-Trained Models from TensorFlow
Keras H5 Import Pre-Trained Models from Keras
PMML Import traditional machine learning models
ONNX Import from Caffe2, PyTorch, Apache MXNet, and Other Frameworks.
DataVec Transforms Data ETL Normalization and Vectorization Pipelines
SKIL Platform
Model Serving Embeddable Model Hosting, Management, and Version Control LIMITED
Multi-Node Support Distribute training and inference across clusters of servers
Scale Fault tolerance, load balancing, and leader election
Installation Deployable via Docker and Bare Metal on Cloud, On-Prem, or Hybrid Systems.
Model Import Importing Models from Widely Used Machine Learning Libraries
Hardware Acceleration Managed CUDA for GPU and MKL for CPU
Integrations Native Integration with Big Data Tools such as Hadoop and Spark
Application
Robotic Process Automation Add an AI Layer on top of Existing RPA Applications.
AI Infrastructure SKIL is Pre-Packaged on Cisco and Huawei Servers.
Support
Online Community Access to Community Forum, Videos, and Documentation
Development Support General Feature Engineering and Model Tuning Advice
SLA Guaranteed Uptime and Response Times
Cost Free Contact Us

Free Consultation

Schedule a 30-minute Q&A with our AI experts.

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