Synthetic Data Generator

Build applications with the data you can trust

Train models and test applications without complaining about data scarcity, exposing sensitive and restricted data.
Privacy regulations, security constraints, bias, and lack of data often prevent teams from using real production data for training, testing, and collaboration. SDG generates privacy-safe synthetic data that behaves like real data preserving all statistical relationships between different entities - without loosing the data patterns, relationship
or exposing it.

Teams can move faster, collaborate more effectively, and share safely.

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Capabilities

Built for Enterprise-Grade Synthetic Data Generation

A complete platform covering every dimension of modern enterprise data — from structure to semantics.

Lifecycle-Centric Design

A structured approach spanning discovery, agent-type selection, development, testing, deployment, monitoring, and continuous improvement.

Relationship-Aware Generation

Maintain business logic and relationships across linked entities — referential integrity included.

Time-Based Data Creation

Model complex trends, seasonality, and anomalies to simulate realistic temporal patterns across datasets.

Bias & Imbalance Correction

Improve model fairness and robustness through class balancing and intelligent imbalance mitigation techniques.

Text & Semi-Structured Data

Work seamlessly across modern enterprise data types — JSON, logs, unstructured text, and beyond.

Teams Move Faster

Collaborate more effectively and share safely — accelerate every team without compromising compliance or control.
Where Teams Use It

Built for every stage of the AI lifecycle

From experimentation to production, SDG accelerates every team — without compromising on data trust.
See how it works

Model Training & Fine-Tuning

Feed AI models with high-volume, high-quality synthetic data that mirrors real production patterns.

Application Testing

Run comprehensive QA cycles with realistic, edge-case-rich datasets — without touching real user data.

Responsible Data Sharing

Share data across teams, vendors, and partners without legal or compliance exposure.

Rapid Experimentation

Unblock data science teams with on-demand synthetic datasets to test hypotheses in hours, not weeks.
Data

Data risk is now business risk

As AI moves into production, organizations must balance speed with trust. Synthetic data that mirror real-world patterns, enables teams to accelerate training and testing - without exposing real records or compromising compliance, privacy, or control
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CAPABILITIES
Agentic Systems Engineering Agile Practice Cloud Engineering Context engineering Data Engineering DevSecOps Digital Engineering Eval Engineering Harness Engineering Human-in-the-Loop Engineering Information Security Knowledge Graph Engineering Salesforce Semantic Layer Engineering Site Reliability Engineering → (SRE)
SERVICES
Agentic Workflow Automation Al/GenAl ALTi Ai adoption LAB Data Modernization Digital Business Digital Enterprise Digital Operations Intelligent Infra Knowledge Graph/Ontology Platform Modernization Predictive AI/ML Analytics Secure & Compliant AI

Sectors
Automotive BFSI Life Sciences Manufacturing Payments & Fintech Retail & CPG Regional Banking Modernization

Partner Ecosystem
Anthropic
AWS Azure Databricks Google Cloud Open AI Salesforce Snowflake

RESOURCES
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About Us Case studies Events Press

Head Office

USA (Southfield) - HQ
2000 Town Center, Suite 170
Southfield, MI 48075
+1 248-281-2500

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