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title: README
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DBbun LLC creates original, high-quality synthetic databases for research, analytics, and machine learning. Each dataset is generated from first-principles simulation and generative models, producing structured, realistic data without relying on real-world records. DBbun’s databases are fully privacy-free, reproducible, and designed for large-scale experimentation, benchmarking, and scenario analysis.
See DBbun listed as a contributor on the DARPA Lift Challenge Contributor Portal.
Read Articles:
- Introducing DBbun: Synthetic Data for a Data-Hungry World
- From Story to Dataset: Turning Speculative Fiction Into Data
- From EMRBots (2015) to Clinically-Informed Synthetic Patient Populations (October 2025)
- How AI Turns a Neighborhood Into a 400-Year Story
- An AI-Created Vision of 2045 Health Sensing
- Bio-Inspired Engineering for the 2026 DARPA Lift Challenge
- What 1,000 Synthetic Missions Reveal About Superior Aircraft Design?
- What If Every Research Paper Had an Associated Dataset?
- What Happens When a 20-Year-Old Idea Is Freed from the Lab?
Contact: contact@dbbun.com