HiddenLayer
2026 AI Threat Landscape Report Backed by patented technology and industry-leading adversarial AI research, our platform provides AI Discovery, AI Supply Chain Security, AI Attack Simulation, and AI Runtime Security. Developers are embedding AI into tools and workflows faster than security teams can track, leaving blind spots that grow before anyone notices. Third-party models introduce unknown code and vulnerabilities, and it’s hard to secure what you didn’t build yourself. Traditional tools can’t test or predict how applications behave under pressure, making it hard to know if your defenses actually work. Most organizations lack the tools and plans to detect or respond when AI systems are compromised. Our platform proactively defends against the full spectrum of AI threats, safeguarding your IP, compliance posture, and enterprise operations. Identify and build an inventory of the AI applications, models, and assets in your environment. Analyze, identify risks, and protect your AI applications, models, and assets as you build. Continually identify threats and validate defenses to safeguard agentic and generative AI applications at scale. Firewall to monitor, detect, and respond real-time to adversarial threats on agentic and generative AI applications. Simplified deployment with pre-built integrations into CI/CD, MLOps, Data Pipelines, and SIEM/SOAR. Reduction in exposure to AI exploits Disclosed through our security research Secure your AI with precision-built defenses. Detect hidden risks in third-party and proprietary models. Identify threats early and validate defenses continuously. Prevent misuse, data leakage, and adversarial attacks with policy-based controls. Safeguard autonomous systems and protect against rogue behavior. Address your AI Security needs by a specific industry or role. Securely Innovate with AI for Fraud Detection, Trading, Compliance, and Customer Engagement. Accelerate AI innovation, safely and confidently. Protect Agentic, Generative, and Predictive AI Systems for Mission Assurance. Enable Safe and Scalable AI Adoption. Build AI applications securely without compromising speed or flexibility. As enterprises embrace AI, security can’t be an afterthought. HiddenLayer makes it possible for CISOs to lead with confidence and keep innovation secure. Securing AI requires protection across the entire lifecycle. HiddenLayer delivers end-to-end visibility and defense so CISOs can safeguard AI at every stage. Strong governance is critical as AI becomes embedded across enterprises. HiddenLayer provides the comprehensive framework needed to manage risk and align AI adoption with visibility, compliance, and accountability. The integrity of AI systems is as critical as the integrity of our software supply chains. If we can't secure the building blocks of AI, we risk exposing enterprises to new classes of attack. HiddenLayer is tackling this problem at its root, delivering the protections the world nee
Vijil
Cut time-to-trust in AI agents from 6 months to 6 weeks. Vijil makes agents reliable, secure & safe for enterprises with testing & protection.
To help enterprises use AI agents that are verifiably reliable, secure, and safe by providing trust as infrastructure for agent development, operations, and continuous improvement. Previously GM Director of Engineering at Amazon SageMaker. 30y across AI/ML, Data, Cloud, OS, Security; 11 AWS AI services, 30 products, 10 patents, 5 papers. AWS AI senior leader; 20y in ML systems and graphics; led PyTorch, TensorFlow, and AWS SageMaker Training teams. Previously COO at Astronomer; helped scale Lacework from $1M to $100M ARR; 20y GTM strategy partnerships for cybersecurity; consulting and investment banking; Harvard. Assistant Professor of Statistical Sciences at the University of Toronto, a Faculty Member at the Vector Institute for Artificial Intelligence, and a Faculty Affiliate at the Schwartz Reisman Institute for Technology and Society. Responsible AI leader; 10y+ in data science; co-author Trustworthy ML (O'Reilly book); 40 papers, 20 patents; key contributor to OSS (Garak, AVID, AI Village). Previously at Amazon Music,Oracle, and Viiv Labs; co-founder CTO of Adya (acquired by Qualys). Passionate about designing and building large-scale ML systems with a focus on NLP/LLMs. Enjoys reading, hiking, cooking, doing nothing. Previously at Riva Health, Viiv Labs, Solvvy, and Polycom. Over 20 years of software engineering experience. Most recently, led threat modeling and cybersecurity analysis of medical device to prepare for FDA approval. University of California, Berkeley. Previously at CapitalOne, evaluating LLMs for company-wide use. Working in the field of responsible AI since 2019, including building explainability solutions, establishing responsible AI processes, and publishing interdisciplinary research at venues like FAccT. Tries to spend at least one week a year walking in the mountains. UX/UI design and front-end developer, previously at bitlogic.io. Based in Cordoba, Argentina. Instituto Superior Politécnico de Córdoba. Previously at Amazon, Oracle, and Accenture. Working on AI/ML security engineering since 2019. Most recently, led red-teaming for Amazon AI models. Indiana University. Cloud infrastructure engineer. Most recently at MIST (acquired by Juniper), built the conversational interface to Marvis Virtual Network Assistant, designed to diagnose and resolve networking issues. University of Illinois at Urbana-Champaign. Previously at Microsoft. Research interest in trustworthy AI, ML for human safety, and autonomous vehicles. University of Michigan. Senior Applied Scientist. Previously at Lorica Cybersecurity, designed and deployed privacy-preserving machine learning products; expertise in the use of fully-homomorphic encryption and trusted execution environment for LLMs. University of Toronto. At intersection of algorithmic fairness auditing and collective action. PhD UIUC, MS Harvard, BS Caltech. Previously at Goldman Sachs, with internships at Instacart and Snap. Previously postdoc in game theory and r
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