The Deterministic
Synthetic Data Platform
Tabular · Healthcare FHIR · Industrial · Physics — with cryptographically-sealed evidence on every run. One platform that covers what other vendors cover at most one of. Provably correct, reproducible on demand, and trusted by regulated organisations.
What Organisations Use RadMah AI For
How RadMah AI Works
Define a contract. Run the engine. Receive synthetic data and an evidence bundle that proves its quality.
Define Your Data Contract
Specify your constraints, schema, and requirements upfront. The contract governs exactly what the engine produces — no surprises, no unchecked outputs.
- Schema and relational constraints defined declaratively
- Feasibility-conditional hard guarantees: zero violations for feasible contracts
- Deterministic by design — cryptographically sealed, bit-for-bit reproducible
Run the Engine
The engine enforces your contract through deterministic constraint enforcement. It generates projections that satisfy all specified constraints — with feasibility certificates when contracts are achievable.
- Zero hard relational violations for feasible contracts
- Reproducible runs with auditable hashes
- Scenario and regime-aware synthesis for complex systems
Receive Projections + Evidence
Every run produces two outputs: the synthetic data (projections) and a comprehensive evidence bundle. The bundle contains constraint, determinism, utility, and privacy risk reports — so you can audit exactly what was generated and how.
- Constraint Report: which rules were enforced, which were relaxed
- Determinism Report: reproducibility hashes and seed state
- Utility Report: statistical fidelity and distribution quality
- Privacy Risk Report: measured and reported, not assumed
Platform Capabilities
Four pillars — Synthetic Data, Healthcare FHIR, Industrial Simulators, and Developer Platform — covering tabular, clinical, OT/ICS, and programmatic workflows under one tenant-isolated platform.
Mock Data
Instant synthetic data from descriptionsDescribe what you need in plain English. The AI drafts a typed schema, generates production-realistic records with domain-appropriate values. No training data required. No uploads. No waiting. Industry-leading accuracy on public tabular benchmarks.
Synthesize
Train on your data, generate faithful replicasUpload your real CSV. The platform trains our synthesis engine on your data — learning distributions, correlations, and tail behaviour. Generate unlimited high-fidelity synthetic rows that preserve the patterns in your original data. Privacy-safe by construction. Industry-leading accuracy on public tabular benchmarks.
Virtual SCADA
Realistic OT data without a single real sensorGenerates streaming telemetry from virtual industrial environments — not statistical approximations, but realistic sensor readings from a deep plant-template library covering all 16 CISA critical infrastructure sectors. Output across 6 live OT protocols: Modbus TCP, OPC-UA, BACnet/IP, MQTT, DNP3, and IEC 61850.
Virtual PLC
Air-gapped OT controller simulation in your VPCSimulate programmable logic controllers entirely inside your own infrastructure. Ships as an air-gapped Docker image that runs in your VPC — no external connectivity required. Pairs with Virtual SCADA for realistic end-to-end OT environments without touching a physical PLC.
ICS Security
The most realistic ICS attack data available outside a live networkGenerates labelled cybersecurity telemetry for industrial control system environments — realistic normal operational baseline traffic alongside sophisticated multi-stage attack sequences mapped to MITRE ATT&CK for ICS techniques, with ground-truth classification at the record level. Purpose-built for the data gap no other tool fills.
Constrained Synthesis
Data that obeys your business rulesGenerate synthetic data with hard constraints that are mathematically guaranteed — monotonicity, sum bounds, referential integrity, rate limits. No violations possible. Designed for financial, clinical, and actuarial data where constraint violations invalidate the entire dataset.
Healthcare FHIR
HL7 FHIR R4 bundles with zero PHIGenerate HL7 FHIR R4 bundles for healthcare development, validation, and compliance workflows. Shipped clinical vocabularies, core resource types, and 100% referential integrity by construction. Zero PHI in output — statistically derived, not anonymised.
AI Assistant
Plain-English driver with cost gatesPlain-English interface to every capability. Specify your job in natural language, review the cost estimate, approve execution. Every conversation is transcribed and cryptographically sealed — no hidden actions, no untraceable workflows.
Autonomous Data Scientist
Autonomous multi-step pipelines with human approval gatesThe only autonomous data science agent purpose-built for ICS/OT security. State a goal in natural language, approve the plan, and receive a cryptographically sealed, evidence-validated dataset. Evidence-based self-healing when results fall short — every decision BLAKE3-chained into an auditable AI decision trail.
Build on RadMah AI
Every capability on the platform is accessible from a typed SDK, a versioned REST API, and signed webhooks. No UI-only workflows — everything you can do in the app, you can do in code.
Connectors for warehouses, RDBMS, object storage, and model hubs are signed, tenant-scoped, and operate under the same evidence contract as interactive runs. Full developer documentation, OpenAPI spec, and example notebooks live on the RadMah AI product site.
Evidence Bundles
Every generation run produces a structured evidence bundle — a product primitive that proves the quality and integrity of your synthetic data.
Constraint Report
Documents which constraints were enforced, which were relaxed, and the feasibility status of the contract.
Determinism Report
Reproducibility hashes, seed state, and run metadata so you can replay any generation exactly.
Utility Report
Statistical fidelity metrics — distribution quality, correlation preservation, and edge case coverage.
Privacy Risk Report
Privacy measured and reported. No absolute claims — quantified risk assessment with methodology.
Core Capabilities
Constraint Enforcement
Zero hard violations for feasible contracts, enforced by deterministic constraint enforcement.
Evidence Bundles
Every run produces auditable proof: constraint, determinism, utility, and privacy risk reports.
Cryptographic Sealing
Every dataset is cryptographically sealed at the moment of generation. The output is bit-for-bit reproducible — provably identical, independently verifiable.
Scenario & Regime Engine
Scenario and regime-aware synthesis for industrial and complex relational systems, with explicit transitions.
Reproducible Runs
Reproducible runs with auditable hashes and evidence bundles. Replay any generation for QA, validation, or security.
Privacy by Evidence
Privacy measured and reported — evidence over claims. No absolute guarantees; quantified risk assessment instead.
Fidelity vs Integrity vs Truth
Most synthetic data tools optimise for statistical fidelity alone. RadMah AI distinguishes between three qualities — and lets you decide which matters most for your use case.
Fidelity
Statistical resemblance to real-world distributions
Integrity
Relational and constraint correctness across tables
Truth
Auditable evidence that proves what was generated and how
What Makes RadMah AI Different
The synthetic data market is growing. RadMah AI occupies a distinct position — and the distinction matters.
Other tools generate data. RadMah AI generates data and proves it.
Tools that generate data without evidence ask users to trust the output. RadMah AI generates evidence that makes trust unnecessary — the output can be independently verified, and the evidence makes that verification straightforward.
Other tools treat determinism as a feature. RadMah AI treats it as a requirement.
Determinism in other platforms means consistent output. In RadMah AI it means the output is cryptographically proven to be consistent, and the proof is attached to every dataset automatically.
Other tools serve general use cases. RadMah AI is purpose-built for regulated and industrial environments.
The Virtual SCADA, the ICS Security, and Synthesize are not adaptations of general-purpose tools. They are capabilities built specifically for operational technology, industrial cybersecurity, and regulated research.
Other tools require expertise to operate. RadMah AI's AI assistant makes it accessible to any team.
Domain experts can describe what they need in domain language and get verified output without becoming synthetic data specialists. The assistant handles specification, routing, execution, and review.