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.
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
Choice of Local AI Engine Models
Local AI Engine now offers two models: Precision, the default, and Express, which is about 10 times faster but less accurate on text with broken spacing or non-Latin characters. Express requires Local AI Engine 1.26.11.0 or later.
AI Detection Cache
Setting cache_ai_detect_spans to true makes later runs send only new or changed text to the AI Engine, speeding up repeat runs. The cache stores only text hashes and detected entity positions, so it holds no PII. It is off by default and can be cleared at any time.
Singapore NRIC Checksum
A new singapore_nric checksum supports Singapore NRIC/FIN numbers in set_checksum, checksum_valid, imitate_unique and from_unique_imitate.
Date Format Preservation in Unstructured Text
Breaking change: unstructured_text masks now preserve the source date format by default. A from_random_date followed by a typecast with no date_format writes dates such as 1st of January 2025 instead of 2025-01-01, and a from_random_date with epoch parameters is now refused. A typecast with a date_format is unchanged, and setting enabled: false under date_format_preservation restores the previous behaviour.
Up to 10x Faster AI Detection
ai_detect masking is now up to 10 times faster in mask_table tasks and most mask_file formats. The documentation describes what is covered and how to set workers and batch_size.
Faster PDF Masking
PDF masking is now faster, and masked PDFs are smaller.
Deprecated ai_detect Guidelines
The guidelines setting of ai_detect is deprecated and no longer sent to the AI Engine. Rulesets that still set it run with a warning, so use self-explanatory names for custom labels instead.
Live Run Logs Updates
The Run Logs page now updates the status and duration of runs in progress without a refresh.
DocumentDB Run History
Run history is now recorded for Amazon DocumentDB connections created through the API.
Broader Connector Compatibility
Improved compatibility with Amazon Redshift, IBM Db2 LUW, IBM Db2 for i, Databricks and Amazon DynamoDB connections.
Timestamptz Time Zone Fix
Fixed PostgreSQL and Databricks Lakebase timestamptz values being masked as UTC when the server, role or database time zone is not UTC. This corrects the output of masks such as retain_year and retain_age, and table_reference lookups on those columns now find rows.
Cross-Schema Foreign Key Fix
Fixed Oracle schema discovery and masking runs failing when a schema has a foreign key to a table in another schema. Masking runs on MySQL, MariaDB, Amazon Redshift and IBM Db2 LUW now also handle such foreign keys correctly.
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 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.
DataMasque helps enterprises accelerate development, testing, analytics and AI with synthetically identical customer data. Fully functional, realistic and privacy compliant.
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
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.