Synthetic Data
You Can Prove
SynthLabTech synthesis engines learn the joint probability distribution of your real data and generate new records that preserve marginal distributions, inter-column correlations, and tail behaviour — with cryptographic evidence proving every claim.
Synthesis Capabilities
Each capability targets a different synthesis regime. The platform automatically routes your contract to the optimal capability based on schema structure, column types, and constraint requirements.
Describe what you need in plain English. The AI drafts a typed schema and generates production-realistic synthetic data with domain-appropriate values — instantly. No uploads, no training data, no waiting.
- Natural language to synthetic data in seconds
- AI-drafted schema with automatic type inference
- Domain-aware value generation (names, addresses, dates, financial, clinical)
- Industry-leading accuracy on public tabular benchmarks
Upload your real CSV. The platform trains our synthesis engine on your data — learning distributions, correlations, tail behaviour, and rare events. Generate unlimited faithful synthetic rows. Privacy-safe by construction.
- Upload CSV — platform trains automatically
- Preserves joint distributions and column correlations
- Tail behaviour and rare events faithfully reproduced
- Constrained synthesis available for hard business rules (monotonicity, sum bounds, referential integrity)
Stream realistic OT telemetry across 6 live industrial protocols — Modbus TCP, OPC-UA, BACnet/IP, MQTT, DNP3, and IEC 61850. A deep plant-template library covering all 16 CISA critical infrastructure sectors. Cyber-range output with pcapng captures.
- 6 live OT protocols with wire-level fidelity
- Deep plant-template library across all 16 CISA sectors
- Validated industrial physics behaviour per vertical
- Pcapng wire captures, NDJSON telemetry, Parquet signals
Generate ground-truth labelled ICS attack datasets mapped to MITRE ATT&CK for ICS. Realistic attack traffic for IDS training, SOC validation, red/blue team exercises, and SIEM tuning — with full causality chains and blast radius propagation.
- MITRE ATT&CK ICS-mapped attack techniques
- Full causality chains with blast radius propagation
- Configurable normal-to-attack traffic ratio
- Integrates with live Virtual SCADA simulations
Quality Metrics in Every Generation
Every synthetic generation includes a full statistical quality report — delivered as part of the sealed evidence bundle.
KS Similarity
Kolmogorov-Smirnov test per column. Compares the empirical distribution of synthetic output against the real reference distribution.
Correlation Preservation
Inter-column Pearson correlation matrix comparison. Synthetic data must preserve the joint dependency structure of the real dataset.
Privacy Metrics
Re-identification risk scores, k-anonymity measurements, and nearest-neighbour distance analysis between real and synthetic records.
Utility Report
Statistical similarity metrics — marginal fidelity per column, distribution comparisons, and downstream model performance parity.
Audit-Ready from Day One
GDPR, HIPAA, and sector-specific regulations restrict how personal and sensitive data can be shared, moved, or used for development and testing. SynthLabTech resolves the access bottleneck without compromising compliance posture.
Start generating distribution-faithful synthetic data
SynthLabTech is available today. Visit the product site, or explore the full platform to see what each engine produces.