K2view Synthetic Data Generation Tool

AI Generation

Generates realistic synthetic data from patterns learned from masked production data. Best for production-like volume and statistical fidelity.

Rules-Based Generation

Generates targeted datasets from defined business rules, without relying on production data. Best for new functionality, edge cases, and negative testing.

Data Cloning

Replicates complete business entities at scale while preserving relationships across systems. Best for load, performance, and high-volume testing.

Intelligent Data Masking

Replaces sensitive production values with realistic alternatives while preserving data relationships. Best when real data is useful but must be made compliant.

Entity-based, not column-based

The entity data model is the blueprint for generation, so synthetic data keeps its relationships and referential integrity across every system.

Every generation method, one platform

AI, rules, cloning, and masking in one product, blended per scenario instead of forced into a single method.

No ETL, end to end

One platform handles everything around generation, prep and masking before, provisioning and refresh after, all compliant, no ETL tool required.

From test case to synthetic data, autonomously.

A K2view data agent reads your test cases and determines the test data required for full coverage. The agent then selects and configures the right generation methods, executes them , and provisions the synthetic entity data to the downstream environment.

The result: one complete, compliant dataset, with referential integrity, ready for your test cases.