Cortexa Labs develops Robusto, an AI diagnostic and maintenance tool that stress-tests models, finds failure points, and generates targeted synthetic data to improve real-world robustness.
Post-training model hardening and monitoring. We probe adversarial, drift, and distribution-shift failure modes, generate targeted synthetic data, and can run short fine-tunes to deliver patched weights with an audit-ready robustness report.
Teams shipping ML in healthcare (medical imaging), financial services/fraud, and other regulated use cases that need measurable robust-accuracy gains without architecture changes.
AI risk management requirements are rising across model risk, safety, and privacy. Buyers need measurable robustness improvements they can show to auditors.
Backed by Fusen with an active prototype, public product site, and benchmark-led validation on adversarial robustness.
Cortexa Labs, Inc. is backed by Fusen.
Part of leading startup programs, founded by Georgia Tech alumni.