Solumn AI Information

Solumn turns AI safety research into measurable changes in how a frontier model behaves. Safety and alignment research produces threat models, techniques, and findings. Converting those into a safer model is a separate and harder problem. It takes training data built to the right specification, evaluations that isolate the behavior you actually care about, and scoring you can trust. That work is hardest in the settings where capability is advancing fastest, namely agentic tasks, tool use, and code, and it rarely scales at the pace a release demands. This is what we do. We build human-curated safety datasets for post-training and evaluation environments that reflect how models are really used, and we run red teaming that surfaces the failures a model conceals under pressure. Every evaluation ships with a verifier designed to resist gaming, so a passing result reflects genuine capability rather than a shortcut. We work as an extension of a lab's safety and alignment teams, adding capacity and an outside read rather than acting as an auditor.