HiddenLayer's "MLSec" Platform offers tools to monitor the performance and operations of enterprise ML/AI models and linked applications in real-time, scanning vulnerabilities and offering recommendations for hardening them. The company also provides consulting services from its team of Adversarial Machine Learning (AML) experts. HiddenLayer plans to use the new funding to hire an additional 40 personnel by the end of the year and continue expanding its client base.
Key takeaways:
- HiddenLayer, a cybersecurity startup based in Austin, Texas, has raised $50 million in a Series A funding round. The round was led by M12 and Moore Strategic Ventures, with participation from Booz Allen Ventures, IBM, Capital One, and TenEleven.
- The company provides tools to safeguard AI/ML models used by enterprises, without accessing the models or compromising proprietary data. The tools monitor the performance and operations of ML/AI models and linked applications in real-time, scanning for vulnerabilities and offering recommendations for hardening them.
- HiddenLayer also offers consulting services from its team of Adversarial Machine Learning (AML) experts who can perform threat assessments, training for a client’s cybersecurity and dev ops personnel, and perform “red team” exercises to ensure the client’s defenses are working as intended.
- Earlier this year, HiddenLayer partnered with Databricks, allowing Databricks enterprise customers to use HiddenLayer’s MLSec Platform directly on their models running on Databricks’ lakehouses.