Sold by: VITech LabÂ
Deployed on AWS
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Generate highly accurate product demand predictions at scale in the cloud
Overview
The Product Demand Forecasting Solution is a cloud-native predictive analytics ML model that analyzes multiple data points, including historical sales data, inventory data, and growth projections to generate up to 50% more accurate product demand forecasts. The solution is scalable and customizable, allows for manual adjustments. It supports batch (schedule) and real-time forecasting, and it can be integrated through RESTful API. The ML model can be used by small- and midsize retailers to cut overstock/stockouts, optimize inventory, and increase supply chain efficiency
Highlights
- Get the most of your organization’s sales and inventory data to accurately predict demand for your products, thereby reducing overstock and stockouts, cutting waste, and increasing profits
- Take advantage of more accurate forecasts to provide the products your customers want when they want them, thereby optimizing product holding costs in warehouses and increasing supply chain efficiency
- Need a custom-made solution for product demand forecasting? Reach us at support@vitechlab.com
Details
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Delivery method
Latest version
Deployed on AWS
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Features and programs
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Pricing
Free trial
Try this product free for 30 days according to the free trial terms set by the vendor.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.c4.xlarge Inference (Batch) Recommended | Model inference on the ml.c4.xlarge instance type, batch mode | $25.00 |
ml.c4.xlarge Inference (Real-Time) Recommended | Model inference on the ml.c4.xlarge instance type, real-time mode | $3.00 |
ml.c4.xlarge Training Recommended | Algorithm training on the ml.c4.xlarge instance type | $3.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $25.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $25.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $25.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $25.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $25.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $25.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $25.00 |
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Legal
Vendor terms and conditions
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Content disclaimer
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Delivery details
Amazon SageMaker algorithm
An Amazon SageMaker algorithm is a machine learning model that requires your training data to make predictions. Use the included training algorithm to generate your unique model artifact. Then deploy the model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Version 1.0 released
Additional details
Inputs
- Summary
Example notebooks for deployment, Real Time inference and Batch Transformation
You can find all the information related to the usage of our product here: https://github.com/VITechLab/aws-sagemaker-examples/tree/master/ForecasterÂ
This repository contains example Jupyter Notebooks showing how to train and deploy the model, run Real Time inference, run Batch Transform job to perform the inference on the data stored in Amazon S3 bucket.
Supported request content type for training is “text/csv” Supported request content type for prediction is “application/json” Supported response type for prediction is “application/json”
You can find more details here: https://github.com/VITechLab/aws-sagemaker-examples/tree/master/ForecasterÂ
- Input MIME type
- application/json
See Input Summary
See Input Summary
Resources
Support
Vendor support
If you have any issues or feature requests, please write to us, and we will be happy to help you as soon as possible. We can also create custom software and models optimised for your specific use case. Reach us at: support@vitechlab.comÂ
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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