Kingfisher: The Synthetic Data Generator

First, let’s understand what is synthetic data, synthetic data is artificially generated data that mimics real-world datasets. It helps businesses de-risk compliance and data security by eliminating the need to use actual production data in non-production environments.

Synthetic data is artificially generated data that mimics real-world datasets. It helps businesses de-risk compliance and data security by eliminating the need to use actual production data in non-production environments. Synthetic data generation tools create realistic, production-quality data without using any actual production data. Synthetic data generation tools simulate the statistical properties, relationships, and patterns of real datasets, allowing teams to test, train, and validate systems safely. They help businesses eliminate compliance risks, protect sensitive information, and accelerate innovation, especially in regulated industries where data privacy is critical.

Kingfisher serves as a powerful test data generator tool that produces schema-compliant, generated synthetic datasets for testing, validation, and migration. It empowers QA testers and analysts to simulate production-like conditions without risking sensitive data exposure.

Unlike other tools, Kingfisher can generate data from code, schema, or existing datasets. It also supports data profiling and enrichment to make every generated synthetic dataset reflect real-world complexity while staying bias-free and compliant.

Zero coding, REST API integration, bulk DDL/DML ingest, complex data type support, and data profiling. It also supports AI/LLM (e.g. OpenAI, Gemini) integration, business-aware data creation, and multi-format export (CSV, JSON, Parquet, Avro).

Roles such as Data Scientists, QA Testers, ML Engineers, Compliance Officers, and CIOs benefit most, across departments like Data Science, AI/ML, QA, and Compliance.

Kingfisher tackles data privacy, compliance restrictions, limited data access, high testing costs, and slow delivery cycles by enabling on-demand, secure data generation. Every generated synthetic dataset aligns with the organization’s structure, logic, and compliance needs, removing long-standing data bottlenecks in non-production environments. By eliminating the dependence on real user data, Kingfisher provides fast, safe, and compliant datasets for development, testing, and analytics, ensuring stronger security and significantly faster testing cycles.

Ideal for testing, migration, regression, performance testing, integration testing, and AI/ML model training, wherever quick, schema-compliant, bias-free data is needed.

Kingfisher delivers statistically accurate, bias-free data for training and validating AI/ML models, ensuring data quality and diversity from the start.

Yes — through RESTful APIs, it integrates easily with your existing DevOps, testing, or data platforms for smooth workflow automation.

Kingfisher can write data (output) into files such as CSV, JSON, Avro, Parquet, and Fixed-width, as well as into databases and cloud storage systems.