Improve data quality for coding LLMs

Large language models are powerful but inherit flaws from their training data. SonarSweep is a service engineered to systematically remediate, optimize, and secure coding datasets for model training. It proactively ensures that models learn from high-quality, and secure examples, from pre-training to model alignment—an essential step to building reliable AI coding models. Models trained on data prepared by SonarSweep produced code with up to 67% fewer security vulnerabilities and up to 42% fewer bugs compared to models trained on the original, un-swept data, without loss in functional performance.