Prove your detection engine works. Then keep proving it.
Generate production-like synthetic sensitive data at scale, then benchmark your scanner's output against ground truth. The result is an independent, third-party accuracy report you can put in front of clients and auditors.
Enterprises rely on your engine or scanner to find sensitive data. How do you prove it does?
Hand-built samples cover a few formats and a few fields. They miss the variety that real environments throw at your scanner.
It never quite reflects real-world sensitive-data distributions, and using it still carries compliance risk.
Prospects and auditors want independent proof of precision and recall, not a figure from your own test suite.
Realistic test data, on demand.
Production-like synthetic sensitive data across 23+ categories and 200+ subcategories, with multiple document templates per category and wide permutation coverage.
23+ categories · 200+ subcategories
The most comprehensive coverage available, spanning Healthcare, Financial, Legal, Government, Insurance, Gaming, Telecom, Energy, Logistics, Automotive, Education, Travel and more, with multiple document templates per category.
Filter-based document generation
Select exactly which PII / PHI fields appear in any template from the dashboard. The system generates a properly formatted document with only those fields, for precise, scenario-specific validation.
Output formats & document size
Generate in DOCX, PDF and scanned-image formats, the last for OCR test coverage. Single documents scale up to 50 MB, so you can stress detection on large, realistic files, not just small samples.
Control the data sensitivity & scale
Control the exact percentage of each sensitive-data category to mirror any real-world environment, produce up to 15M unique variants, and re-download any previous dataset from history at any time.
Only the fields you're testing. Nothing else.
In an Offer Letter, choose only Name, Salary and DOB, and neoSim Data generates a properly formatted document containing just those fields. It's precise ground truth for exactly the scenario you want to validate.
- Pick fields per template from the dashboard
- Every value is labelled for ground-truth scoring
- Export as DOCX, PDF or scanned image
Two generation modes.
Enterprise Repository
Push generated datasets straight into your own cloud storage for team access and scale.
Download Zip
Export the full dataset as a Zip for offline storage and air-gapped, self-contained testing.
Independent, ground-truth accuracy proof.
Generation is only half the story. Once your scanner runs against our datasets, the benchmarking platform turns raw output into a credible accuracy report you can share with a prospect or auditor instead of a self-reported number.
- Third-party accuracy reports to share with prospects: proof, not self-reported claims.
- Track improvement over time with a repeatable, comparable benchmark for every scanner version.
- Standardized scoring: Precision, Recall and Compliance against recognized synthetic datasets.
- White-label export (Enterprise tier) for client-ready documentation and audit submissions.
Privacy-preserving by design. Generation and scanning run inside your own environment. You can run your scanner on data files in cloud storage, or upload your scanner output in JSON format for the benchmarking report. No real customer data is involved at any stage, so validating your engine carries no compliance risk.
Generate. Scan locally. Prove accuracy.
Generate the dataset
Pick categories, field filters and data mix. Produce up to 15M labelled variants, then store them in the cloud or export them offline.
Run your scanner
Your scanner engine scans the data inside your own environment or scans on cloud data storage files, so nothing sensitive leaves.
Get the accuracy report
Upload your output in JSON format and receive an independent, auditable benchmark for each release.
One platform replaces manual test-data creation and sanitized production data that never quite reflect real-world sensitive-data distributions, and gives every scanner release an independently verified, auditable accuracy report.
Beyond data masking.
Masking and hand-written scripts were never built to prove a detection engine. Here is how they compare.
| Manual scripts | Masking tools | neoSim Data | |
|---|---|---|---|
| Realistic sensitive data | Partial | ✓ | ✓ |
| 23+ categories out of the box | ✕ | ✕ | ✓ |
| Adversarial & edge-case variety | ✕ | Partial | ✓ |
| OCR-degraded scanned documents | ✕ | ✕ | ✓ |
| Zero real data in the pipeline | ✓ | ✕ | ✓ |
| Ground-truth labels included | ✕ | ✕ | ✓ |
| Independent accuracy report | ✕ | ✕ | ✓ |
Faster, safer, provably compliant.
Faster releases
Test data in minutes instead of a request queue measured in weeks.
Lower breach exposure
No real records in non-production means far less to leak or explain.
Lower cost to run
No masking pipeline to build, maintain and revalidate every quarter.
Proof for buyers
Walk into enterprise deals and audits with evidence, not assurances.
real customer records used to produce any dataset. By design, not by policy.
Built for every product team.
One platform, wherever sensitive test data is the bottleneck.
DSPM & DLP platforms
Stress-test scanners and classifiers with adversarial, production-like data, then prove accuracy with an independent benchmark.
FinTech & payments
Test fraud, KYC and payment flows against realistic financial data, without real account data ever entering test.
HealthTech & EHR/EMR
Validate clinical and claims workflows with synthetic PHI. No real patient records required and no HIPAA exposure.
Any software product
Replace sanitized production extracts for staging, QA, load testing and demos, at any scale and on demand.
neoSim Simulate
Simulate the storage, identity and collaboration systems your scanner connects to, like S3, SharePoint and Okta, with no vendor sandbox.
Ready to see a live benchmark run against your own scanner?
A 30-minute walkthrough shows generation, scanning and the accuracy report end to end.