Synthetic Data Generation at Enterprise Scale
Semantically Rich. Domain-Aware. Production-Ready.
Generate synthetic data that understands your business, not just your schema, while ensuring technical accuracy and contextual relevance.
The Problem with Today's Synthetic Data Tools
Tools that read your schema don’t understand your business; they generate structurally valid but semantically meaningless data.
Schema-Only Output
Generates rows that match column types but have no domain meaning, producing random values, impossible ranges, incoherent data combinations.
No Domain Intelligence
Doesn't know that 'AUM' aggregates holdings, or that a 'SETTLED' trade must have a counterparty. It just fills cells.
Broken Referential Logic
Foreign keys link rows but the relationships make no business sense by creating portfolios without managers, trades without instruments.
Our Approach: Semantic-First Synthesis
We generate data that understands your business, not just your schema. SynthDataGen builds a semantic model of your domain before generating a single row. Each capability addresses a key limitation of traditional schema-only synthetic data tools.
Model the Business First
The Business Ontology Engine maps your business concepts, hierarchies, and rules before generating any data, ensuring every value reflects real business context.
Read Every Column as a Business Concept
'ccy' becomes an ISO 4217 settlement currency, AUM aggregates holdings, and every settled trade includes its counterparty.
Generate Relationships, Not Just Rows
Joins reflect real business relationships, ensuring correct counterparty chains and valid instrument lifecycles. No portfolios without managers or trades without instruments.
What SynthDataGen Delivers
Six capabilities that make synthetic data safe, coherent, and genuinely useful.
Business Ontology Engine
Builds a domain model before generating a single row: concepts, hierarchies, and rules encoded up front.
Schema-to-Business Mapping
Every column understood as a business concept: not 'ccy' but 'ISO 4217 settlement currency'.
Referential Integrity
Joins that make business sense: correct counterparty chains, valid instrument lifecycles.
PII-Safe by Design
Synthetic values protect real identities structurally, not via masking, but by never touching real data.
Volume & Edge Cases
Configure row counts, date ranges, anomaly rates, null distributions, and stress scenarios on demand
Industry-Ready Templates
Capital Markets, Healthcare, Insurance, Retail with pre-built domain models out of the box.
How It Works
VLink's Semantic Data Layer powers the generator, ensuring synthetic data reflects real business knowledge, not random noise.
Your Inputs
Test with data that behaves like production without the production risk.
Schema-valid · Semantically coherent · Business-rule compliant · PII-free
FAQs
What is SynthDataGen?
How is SynthDataGen different from other synthetic data tools?
Does SynthDataGen use or expose our real data?
What inputs does SynthDataGen need?
Which industries are supported out of the box?
How do we get started with SynthDataGen?
What Our Clients Say
Real feedback from organizations we've partnered with
Rick Brady
Client Partner- State of CT; Head of US Health & Human Services (HHS)- Infosys Public Services
VLink consistently goes the extra mile to present only top-quality candidates. It saves me time and sets every project up for success — making VLink my go-to partner whenever I nee...
Awards
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