Sold by: DataMasque
Deployed on AWS
AWS Free Tier
DataMasque for Guidewire Cloud enables insurers to de-identify sensitive Guidewire policyholder and claims data. DataMasque generates synthetically identical data that can be safely used across testing, analytics and AI use cases. Fully functional, realistic and privacy compliant.
3.5
Overview
Insurers need realistic policyholder and claims data to develop new capabilities, improve digital experiences, run analytics and power AI transformation. Using real production data outside of secure environments introduces significant privacy and compliance risk.
DataMasque for Guidewire Cloud enables insurers using the Guidewire Snapshot export service with DataMasque to irreversibly de-identify sensitive Guidewire data, producing synthetically identical data that can then be returned securely to sandbox environments. The result is high-fidelity data that supports development, AI experimentation and transformation without any of the privacy risks.
DataMasque automatically preserves referential integrity across policies, claims and related records, ensuring critical data relationships are maintained for end-to-end insurance workflow testing.
Highlights
- Guidewire Cloud customers deploy DataMasque within their secure AWS environment. A pre-configured automation takes a secure snapshot of the Guidewire instance and, using a pre-defined Guidewire Cloud ruleset, DataMasque replaces sensitive information with synthetically identical customer data.
- DataMasque can preserve referential integrity across Guidewire and other core systems. Policies, claims and related records remain connected and consistent, ensuring full utility and fidelity for end-to-end insurance workflow testing.
- DataMasque's synthetically identical customer data looks and behaves the same way as your real data, maintaining patterns, statistical accuracy and edge cases, without any sensitive information. Irreversible de-identification removes compliance friction from AI development, migrations, software development and third-party data sharing.
Details
Sold by
Categories
Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Rhel 9.4
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
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 the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
guidewire_tb | Guidewire TB | $25,000.00 |
Dimensions summary
This listing uses a single pricing dimension based on Guidewire TB, so you pay according to the volume of Guidewire Cloud data you mask, measured in terabytes. Pricing scales with the amount of data you process rather than by user count or number of masking runs. As your masked data volume grows, your cost adjusts to match. This is a contract-based purchase, so you commit to a term and settle billing through your AWS account for consolidated invoicing.
Top-of-mind questions for buyers
One unit equals one terabyte of Guidewire Cloud data that the software masks. Billing counts the volume of data processed, not the number of users, databases, or masking runs. As the volume of masked data grows, the number of terabyte units you consume increases accordingly.
You can perform masking runs on data of any size. Your cost tracks the terabytes of Guidewire Cloud data you mask, so running more or larger jobs raises the volume billed. There is no separate charge tied to the count of runs.
The software discovers and masks sensitive data using keyword and pattern searches. It applies irreversible masking through a salted cryptographic hash, keeps masked values consistent across sources, and maintains referential integrity for primary, unique, and foreign keys. It integrates with existing CI/CD tools through an API-first design.
datamasque.com+3
Helpful?
Vendor refund policy
Refunds and cancellations are not available.
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
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Azure Cosmos DB Connections
Azure Cosmos DB is now available as a connection type, for request unit (RU) accounts that use its MongoDB API.
Materialise a Table Reference into a Temporary Table
The build_temp_table task can now take a table_reference source, writing a map into a temporary table so a later task can join against it in the database. Available on relational targets except Amazon Redshift.
Pre-Calculated Row Counts
A new pre_calculate_row_counts ruleset option, off by default, logs how many rows each mask_table and mask_unique_key task will mask before masking begins.
Matcher Priority Controls
The unstructured_text mask can now decide which match wins when two start at the same position and have the same length. overlap_handling.matcher_priorities ranks the matcher types, and overlap_priority overrides that ranking for a single entry.
DataMasque Host Instance Tagging
A successful run that changes data now tags the EC2 instance DataMasque is self-hosted on as a DataMasque deployment, where the instance role allows ec2:CreateTags.
XML Comments and Processing Instructions Removed
Masked XML documents no longer carry comments or processing instructions, though the XML declaration is kept. Sensitive data held in a comment, or in editor tracked changes stored as processing instructions, can no longer survive masking.
User Guide Restructure
The Database Connections and Ruleset Specification pages in the user guide are now split into a page per database and per ruleset task. Existing links into the old single pages no longer resolve.
Parquet Unmasked Column Fix
Fixed Parquet file masking altering columns that no rule masks, where large integers lost precision and a stored NaN was written back as a null.
Restricted Page Permission Warning Fix
Fixed the missing permission warning when being redirected away from a restricted page.
Additional details
Usage instructions
Please follow the steps below to complete setting up your DataMasque instance:
-
Access the application via a web browser at https://<instance-ip-or-hostname>. The application may take a few minutes to start. Please refresh the page if you encounter the "Unexpected Error" message.
-
Complete the first-time installation page by providing the following information:
-
Email address of the DataMasque admin user. This email address is stored on the DataMasque EC2 instance and is used for the purposes of providing 'Forgotten Password' account recovery and critical system notifications. DataMasque will not have access to this information.
-
Password for the admin user.
-
Hostnames or IP addresses to access the DataMasque instance.
-
The SMTP settings specific to your organisation.
-
The instance ID of your EC2 instance.
- You will be re-directed to the DataMasque login screen. Please proceed to login with the admin password you have just configured.
Note:
- When you use our software we may receive and store usage data and information relating to the performance and use of the Software. We will not disclose any system information which identifies the user or the user environment to third parties.
- To upgrade your DataMasque version, contact the DataMasque team via https://datamasque.com/contact/?source=support_ticket or support@datamasque.com to request your access to the DataMasque Customer Portal and download the new DataMasque software version.
Resources
Vendor resources
Support
Vendor support
DataMasque provides full product and installation support within 72 hours of making an enquiry. Contact the support team at support@datamasque.com for any enquiries you may have.
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
DataMasque helps enterprises accelerate development, testing, analytics and AI with synthetically identical customer data. Fully functional, realistic and privacy compliant.
DataMasque is a data masking platform that transforms sensitive production data into realistic, fully functional and privacy-compliant datasets.
Its synthetically identical data preserves the statistical characteristics, complexity and edge cases of your original data while maintaining referential integrity and data consistency - without sensitive information ever leaving your secure environment.
A self-contained DataMasque Ready-to-Run Sample Set. Launches with a bundled PostgreSQL database and PGAdmin so you can mask realistic sample data and inspect before/after results in minutes - no setup, no data of your own required.
Deploy DataMasque on AWS for a production-ready, limited-scope implementation that delivers real data masking using your own environment. This reduces compliance risk and builds a foundation for expansion.
This Quick Start engagement covers discovery, configuration, and execution of DataMasque masking jobs across supported AWS databases and file formats. It produces masked, audit-ready datasets and transfers knowledge so internal teams can extend usage independently.
Customer reviews
Shaikshavali K.
Best tool for data masking
Reviewed on Jan 26, 2024
Review provided by G2
What do you like best about the product?
I liked that way it was created to mask business and sensitive data with data masking.
What do you dislike about the product?
It should be better user friendly UI. Performance can also be improved better
What problems is the product solving and how is that benefiting you?
Hiding sensitive data and business data with some data masking techniques.