neoLLM - DSPMTestDataGen
Generate DSPM Test Data with Our Trained In-House LLM
Eliminate manual data creation and auto-generate realistic, ready-to-use DSPM datasets with our trained LLM model.
Data Types
File Types
Meet Our In-House LLM Model
What is DSPMTestDataGen?
DSPMTestDataGen is a fine-tuned, in-house trained LLM designed to generate test data that mirrors real-world sensitive data for DSPM products.
Why it was created?
Created to automate slow, manual test data creation, saving hours of engineering and QA effort.
Key Differentiators
Domain specific to DSPM, with realistic structure and variability, ready for immediate testing.
Who it is for?
QA teams, DSPM solution providers, compliance tool developers, security engineers, and data privacy specialists.
Challenges Our DSPMTestDataGen Solves
Manual Effort
Creating DSPM test data manually is time-consuming; teams spend hours crafting synthetic datasets for each test case.
Solution Highlights
Designed for global usability with extensibility in mind.
- English
- Spanish
- Arabic
Create realistic and structured test data across a wide range of sensitive and regulated data categories.
- PII
- Financial & Payment Data
- Healthcare & Medical Data
- Authentication & Identity Security Data
- Legal & Compliance Data
- Security-Sensitive Data
- Automotive & Mobility Data
- Construction & Real Estate Data
- Corporate Documents
- Education Data
Generate test data in multiple formats to seamlessly integrate with different DSPM tools and workflows.
Supported Formats:
JSON, CSV, XLSX, PDF, DOCX, PPT, and more
Security & Privacy
Frequently Asked Questions
Structured, privacy-safe test data that closely resembles real-world datasets.
Yes. You can generate any type of data directly from the UI by selecting the data you need
No. All output is AI-generated and privacy-safe.
Absolutely. Use it via REST API or CLI wrappers.
Stop Wasting Time on Manual Test Data for DSPM
Talk to our experts and see how our in-house LLM model generates high-quality synthetic data in seconds.













