Sold by: Mphasis
Deployed on AWS
This solution generates a standardized output for input files from various sources containing insurance policy related data.
Overview
This solution can ingest insurance policy data from different sources such as external agencies, brokers, or partners having various schemas/ headers and standardizes them to a fixed output format. This can help business reduce the effort in converting these different files to a format suitable for their consumption. It takes in a CSV file and extracts a set of columns, even if the names are different to generate a Master Data format using the various files.
Highlights
- The solution can be used by various insurance carriers, re-insurance companies etc. in their data sourcing and pre-processing pipelines for processes like KYC, sanction screening etc. The solution is an important enabler to accelerate Master Data Management implementations.
- This solution uses NLP techniques to identify the specific information attributes even if they are mentioned with variation in their names and brings them to a common attribute name.
- PACE - ML is Mphasis Framework and Methodology for end-to-end machine learning development and deployment. PACE-ML enables organizations to improve the quality & reliability of the machine learning solutions in production and helps automate, scale, and monitor them. Need customized Machine Learning and Deep Learning solutions? Get in touch!
Details
Sold by
Delivery method
Latest version
Deployed on AWS
Unlock automation with AI agent solutions
Fast-track AI initiatives with agents, tools, and solutions from AWS Partners.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
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 |
|---|---|---|
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $8.00/host/hour |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $8.00/host/hour |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $8.00/host/hour |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $8.00/host/hour |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $8.00/host/hour |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $8.00/host/hour |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $8.00/host/hour |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $8.00/host/hour |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $8.00/host/hour |
ml.c4.2xlarge Inference (Batch) | Model inference on the ml.c4.2xlarge instance type, batch mode | $8.00/host/hour |
Vendor refund policy
Currently, we do not support refunds, but you can cancel your subscription to the service at any time.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a 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
Initial Release
Additional details
Inputs
- Summary
Input Format
- The solution takes a CSV file as input.
- The dates in the file should be of format YYYY-MM-DD.
- Ensure Content-Type is 'text/csv'.
Input instructions
- The solution works with csv files only.
- The date fields should be in YYYY-MM-DD format only
Output interpretation
- Output file will be a csv that conatins a fixed set of columns from the input csv file.
- The first name, second name columns would be merged
- Different address related columns would also be merged.
Resources
Sample Notebook: https://tinyurl.com/y3mnr2ud Sample Input: https://tinyurl.com/y2569b3k Sample Output: https://tinyurl.com/y3bgcnl2
- Input MIME type
- text/csv
See Input Summary
See Input Summary
Resources
Vendor resources
Support
Vendor support
For any assistance, please reach out to:
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.
Similar products
Claims Assessment Automation - Generate policyholder payout scenarios and recommendations by analyzing complex claims documentation - Requires ingesting and masking sensitive customer medical/financial data (Protector) - High accuracy imperative to provide legally/financially compliant guidance (Enforcer)
Transform your insurance operations with Virtual Office (VO) and Policy Administration System (PAS) by Sonata Software and iNube. These modular, cloud-based solutions are designed for MGAs and insurers to streamline policy distribution, enhance agent productivity, and ensure seamless policy lifecycle management. Now available on AWS Marketplace to accelerate your digital transformation.
LastPass protects sensitive credentials, streamlines account access, and fosters seamless collaboration across the distributed workforce.
For North America and regions outside EMEA, Red Hat Advanced Cluster Security Cloud Service for Kubernetes provides a Kubernetes-native architecture for container security, enabling DevOps and InfoSec teams to operationalize full life cycle container and Kubernetes security.
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.