An advanced Industrial IoT (IIoT) simulator for Smart Factory 4.0 environments using Python, MQTT, and Docker. Emulates configurable production lines with realistic sensor data (vibration, temperature, quality) and predictive alerts.

GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthetic Data Generation

Synthetic data generation for tabular data

Synthetic healthcare data generator for EHR testing and interoperability. Generates realistic, terminology‑backed cohorts with multi‑format export (FHIR R4, HL7 v2.x, VistA MUMPS, CSV/Parquet).

Generate arbitrary queries matching your GraphQL schema, and use them to verify your backend implementation.

🧠 Model-driven synthetic test data for CI/CD and analytics - deterministic, privacy-preserving, and domain-aware. Includes Python APIs, XML pipelines, and MCP/IDE integration to orchestrate realistic datasets for finance, healthcare, and other regulated environments.

[ICCV 2025 Highlights] Large-scale photo-realistic virtual worlds for embodied AI

A novel approach for synthesizing tabular data using pretrained large language models

A library to model multivariate data using copulas.

🚀 AI-powered synthetic data generator that creates educational flowcharts and diagrams using LangGraph workflows. Features FastAPI integration, OpenAI LLM processing, and automated Mermaid diagram generation with iterative quality improvement through reflection patterns.

Conditional GAN for generating synthetic tabular data.

Blackbox provides a standarized and efficient interface for evaluating variety of blackbox functions for various surrogate-based design activities

Reproducible FCC synthetic data factory for transaction monitoring - customers, accounts, transactions, alerts, cases - ready for analytics & model testing.

The official code for "GUI-ReWalk: Massive Data Generation for GUI Agent via Stochastic Exploration and Intent-Aware Reasoning"

Text Embedding Model Fine-Tuning: Generating Data & Fine-Tuning Methods

Synthetic Data Generation for mixed-type, multivariate time series.

EuroStyle Retail Demo - ClickHouse-based multi-database demo platform with realistic business data generation

Generate relevant synthetic data quickly for your projects. The Databricks Labs synthetic data generator (aka `dbldatagen`) may be used to generate large simulated / synthetic data sets for test, POCs, and other uses in Databricks environments including in Delta Live Tables pipelines

Biased dataset generation with intentional unfairness patterns

Python framework for generating streams of labeled data.