Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
Optimize.AI Next Best Action Prediction
By:
Latest Version:
v-5.2
A deep learning based solution to predict the next step and time to next step in a process.
Product Overview
A deep learning based solution that analyzes event (e.g. loan approval process) log data with contextual information (e.g. loan request parameters, etc.) and predicts the next step and time to next step for an open request within a process. With process execution data stored in form of event logs, an AI based operations planning system can help in understanding future system state based on current state and business context. This solution improves business operations planning by reducing cost and improving efficiency through dynamic resource planning.
Key Data
Version
By
Type
Algorithm
Highlights
The solution takes operational log data as input and provides the answers of these questions: o What is the next possible step/request of a given sequence? o What is the approximate time to the next step? The solution provides the mechanism to train as well as test on user data. This allows for the flexibility to build and predict on user specific process data. The solution is divided into two parts:
- Process specific training API to capture process behavior
- Prediction API to predict the next step and time to next step
From a process manager perspective, next best action prediction can be highly useful for resource planning which can help achieve better throughput rate and time at a lower cost. The solution can be applied to various industries like banking, logistics, insurance etc. and processes such as loan approval process, order fulfillment process, procurement process etc.
Mphasis Optimize.AI is an AI-centric process analysis and optimization tool that uses AI/ML techniques to mine the event logs to deliver business insights. Need customized Machine Learning and Deep Learning solutions? Get in touch!
Not quite sure what you’re looking for? AWS Marketplace can help you find the right solution for your use case. Contact us
Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Contact us to request contract pricing for this product.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Algorithm Training$10/hr
running on ml.m5.large
Model Realtime Inference$8.00/hr
running on ml.m5.large
Model Batch Transform$16.00/hr
running on ml.m5.large
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Algorithm Training$0.115/host/hr
running on ml.m5.large
SageMaker Realtime Inference$0.115/host/hr
running on ml.m5.large
SageMaker Batch Transform$0.115/host/hr
running on ml.m5.large
Algorithm Training
For algorithm training in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Algorithm/hr | |
|---|---|---|
ml.m4.4xlarge | $10.00 | |
ml.m5.4xlarge | $10.00 | |
ml.m4.16xlarge | $10.00 | |
ml.m5.2xlarge | $10.00 | |
ml.p3.16xlarge | $10.00 | |
ml.m4.2xlarge | $10.00 | |
ml.c5.2xlarge | $10.00 | |
ml.p3.2xlarge | $10.00 | |
ml.c4.2xlarge | $10.00 | |
ml.m4.10xlarge | $10.00 | |
ml.c4.xlarge | $10.00 | |
ml.m5.24xlarge | $10.00 | |
ml.c5.xlarge | $10.00 | |
ml.p2.xlarge | $10.00 | |
ml.m5.12xlarge | $10.00 | |
ml.p2.16xlarge | $10.00 | |
ml.c4.4xlarge | $10.00 | |
ml.m5.xlarge | $10.00 | |
ml.c5.9xlarge | $10.00 | |
ml.m4.xlarge | $10.00 | |
ml.c5.4xlarge | $10.00 | |
ml.p3.8xlarge | $10.00 | |
ml.m5.large Vendor Recommended | $10.00 | |
ml.c4.8xlarge | $10.00 | |
ml.p2.8xlarge | $10.00 | |
ml.c5.18xlarge | $10.00 |
Usage Information
Training
The deployed solution has these 2 steps: 1.Training API: The system trains on user provided historical process data with contextual information and builds & saves a deep learning model which is a representation of the process behavior.
- Testing API: Once the model is generated, the solution can be used to predict next possible step and time to next step for a given open request within a process.
Channel specification
Fields marked with * are required
training
*Input modes: File
Content types: text/csv
Compression types: None
Model input and output details
Input
Summary
Input
** Following are the mandatory inputs for both the APIs:**
- CaseID: Unique identifier of a request/journey e.g. E-comm order ID, loan ID etc.
- ActivityID: Activity Identifier/Activity Name performed for each CASE_ID e.g. INVOICE GENERATION, KYC etc.
- CompleteTimestamp: Timestamp for a unique CASE_ID/ACTIVITY_ID combination.
- context: Contextual variables can be anything which provides information related to case. E.g. Loan Amount, Vendor ID etc.
Limitations for input type
* Two separate csv input files are required for training and testing
* Test dataset should only contain subset of Activity IDs included in the training dataset
* Maximum sequence length can not be more than 30
Input MIME type
text/csvSample input data
Output
Summary
Output
Content type: text/csv
** The solution generates the following outputs:**
- Case_id: Unique identifier of a request/journey e.g. E-comm order ID, loan ID etc.
- nextStep: Activity Identifier/Activity Name performed for each CASE_ID e.g. INVOICE GENERATION.
- Time(mins): Time to the next step i.e. the time gap between the next step and the previous step.
Output MIME type
text/csvSample output data
Sample notebook
Additional Resources
End User License Agreement
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Support Information
Optimize.AI Next Best Action Prediction
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