Generate Privacy-Safe Multi Modal Synthetic Data in Minutes.
Development, testing, and AI/ML training stall when teams cannot access production data due to privacy regulations, security restrictions, and compliance requirements. 3X Synthetic Data generates production-grade, statistically accurate synthetic datasets across JSON, CSV, relational databases, PDFs, and medical images with zero PII exposure and full GDPR, HIPAA, and PCI-DSS compliance.
Test data shouldn't delay delivery or expose production data.
Every data privacy breach, testing bottleneck, and AI training delay traces back to the same problem: teams need realistic data but cannot safely access production systems. Data masking and anonymization fall short. 3X Synthetic Data eliminates the risk entirely.
Weeks of Manual Test Data Creation
Development, QA, and migration testing cycles delayed by months of manual test data creation. Teams hand-craft datasets row by row, struggle to maintain referential integrity across tables, and still end up with incomplete test coverage. Projects miss deadlines because realistic test data is never ready when the code is.
Unrealistic Test Data
Lack of statistically accurate test data preventing adequate validation of data pipelines, applications, ETL transformations, and migration outputs. Synthetic data generated by basic tools lacks the distributions, edge cases, and cross-table relationships of real production data. Bugs and data quality issues are only discovered in production, not during testing.
Production Data Exposure Risks
Teams copying production data into development and testing environments, exposing real customer PII, financial records, and health data to unauthorized access. One breach can trigger GDPR fines up to 4% of global revenue, HIPAA penalties up to $1.5M per violation, and PCI-DSS compliance failures that block payment processing.
Medical AI Training Constraints
Medical imaging and healthcare AI model training constrained by limited datasets and strict patient privacy regulations. Models underperform due to insufficient training data diversity, and HIPAA restrictions prevent sharing real patient records across research teams, institutions, or cloud environments.
Data Sharing Blocked by Compliance
Inability to share realistic data with offshore development teams, third-party vendors, QA partners, or cross-functional teams due to GDPR, HIPAA, and PCI-DSS compliance restrictions. Distributed development slows to a crawl when every team that needs data has to go through months of legal review and security approvals.
Masking Fails to Prevent Re-Identification
Traditional data masking and anonymization techniques failing to prevent re-identification attacks. Research consistently shows masked datasets can be reverse-engineered to identify individuals through cross-referencing with public data. Synthetic data generated from statistical patterns, not derived from real records, is the only approach that eliminates re-identification risk entirely.
Intelligent generation. Not masked copies.
3X Synthetic Data creates entirely new data from statistical patterns and seed analysis, not masked replicas of production records. Every dataset is statistically accurate, privacy-safe, and production-grade with zero re-identification risk.
JSON and CSV Generation
Create synthetic JSON and CSV datasets from seed data or schema instructions with configurable record volumes, variation strength, and schema complexity. Preserves statistical distributions, value ranges, and field relationships from your source data while generating entirely new records for development, testing, and data pipeline validation.
Relational Database Generation
Generate synthetic data for PostgreSQL, MySQL, SQL Server, Oracle, Snowflake, and Databricks while automatically preserving referential integrity, foreign key constraints, cross-table relationships, and cardinality patterns. Every generated dataset maintains the structural accuracy that integration testing and migration validation require.
Synthetic PDF Document Generation
Produce realistic synthetic PDF documents based on template analysis with varied content, maintaining original layout, structure, formatting, and document logic. Generate synthetic invoices, claims forms, patient records, contracts, and regulatory filings for document processing pipeline testing, OCR validation, and workflow automation without exposing real documents.
Medical Image Generation
Create synthetic X-ray, CT scan, and MRI images with HIPAA-compliant metadata tags that prevent patient identification while providing clinically realistic imaging data for AI model training, diagnostic algorithm development, and medical research. Eliminates the data scarcity bottleneck that limits healthcare AI without compromising patient privacy.
Privacy-Safe by Design
All generated data is 100% synthetic with zero PII exposure at every layer. Not masked, not anonymized, not derived from real records. Generated from learned statistical patterns, ensuring full GDPR, HIPAA, PCI-DSS, and SOX compliance for testing, development, cross-team sharing, and third-party data distribution without legal review or privacy approvals.
Configurable Variation Control
Fine-tune data realism, variation strength, edge case frequency, and statistical distribution to balance accuracy with diversity. Generate datasets that stress-test boundary conditions, null handling, and outlier scenarios for comprehensive test coverage, or produce high-fidelity datasets that mirror production patterns for AI/ML training quality.
From seed data to production-grade synthetics.
A multi-stage intelligent pipeline that analyzes, generates, and validates synthetic data across every format automatically.
- Privacy Constraints
- Compliance Requirements
- No Production Data Access
- Scale Limitations
See exactly what you get.
Every generation run produces structured, validated deliverables. Here's a live preview of what your team receives.
- JSON / CSV
- Database Records
- Quality Report
- Compliance Summary
Every format your team needs. From one engine.
3X Synthetic Data generates privacy-safe data across every major format — structured, unstructured, and visual.
JSON
Nested, complex, configurable
CSV
Flat files, tabular, bulk export
SQL
PostgreSQL, MySQL, Oracle, MSSQL
Templated documents, varied content
X-Ray
HIPAA-safe synthetic imaging
CT Scan
Multi-slice synthetic volumes
MRI
Tissue contrast, multi-modal
Semi-Structured
XML, Parquet, Avro
Privacy-safe data. From day one.
Everything your team needs to generate, validate, and share realistic data across development, testing, and AI training environments without touching production data, requesting privacy approvals, or risking compliance violations.
Minutes to Generate
Create thousands of synthetic records, documents, PDFs, and medical images in minutes instead of weeks of manual test data creation or complex data masking workflows. Every format (JSON, CSV, SQL, PDF, imaging) generated in a single run. Teams get the data they need the same day they need it.
Production-Grade Quality
Statistically accurate synthetic data that maintains business rules, referential integrity, value distributions, cross-table relationships, and realistic edge cases. Data that behaves like production for comprehensive pipeline testing, migration validation, and AI/ML model training, not random values that pass schema checks but fail real-world scenarios.
Zero Privacy Risk
100% synthetic data with no real PII, patient information, financial records, or sensitive content at any layer. Not masked, not anonymized, not derived from real records. Enables fully compliant testing, development, and global data sharing across teams, vendors, and partners without GDPR, HIPAA, or PCI-DSS legal review.
Unlimited Scalability
Generate unlimited synthetic datasets at any volume for testing, validation, analytics, AI training, and demo environments without production data access requests, privacy review cycles, or security approvals. Scale from hundreds to millions of records on demand. Every team gets their own realistic dataset whenever they need it.
See Synthetic Data in Action
Get a personalised walkthrough tailored to your data engineering needs and synthetic data generation challenges.
Let's talk scale.
Our team of engineering experts and AI architects is ready to help you accelerate your data modernization journey.