Denodo is an intelligent data platform that helps organizations deliver live, unified, and governed data for trustworthy AI, analytics, and self-service initiatives. The platform uses logical data management to connect distributed data across hybrid, multi-cloud, on-premises, SaaS, and third-party environments without requiring data movement or duplication. Denodo helps businesses integrate data silos, enable self-service access, enforce governance, deliver real-time insights, and enrich data with business context. It is designed to support agentic AI by giving AI agents accurate, up-to-date, and governed enterprise data for better decisions and actions. The platform includes capabilities such as zero-copy data access, unified semantics, centralized compliance, natural language search, data marketplaces, and optimized query performance.
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Founded in 2004, NetBrain brings Agentic NetOps to enterprise operations with complex hybrid-cloud networks.
Pre-built AI agents grounded in a NetOps Harness, the network context engine, provide governed execution of the entire lifecycle from diagnose, change, and assess to prevent and predict. The platform turns each diagnosis into deterministic automation deployed across your network, eliminating recurring issues faster and at lower cost. Governed execution means agents' actions are grounded before they touch your network, making agentic operations safe and trustworthy. Connect and enrich your cross-domain ecosystem across ITSM, observability, and cloud platforms.
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Mindgard
Mindgard is the leader in AI red teaming, helping enterprises identify, assess, and mitigate real-world security risks across AI models, agents, and applications. Founded on pioneering research in AI security, Mindgard was built on the insight that traditional application security approaches cannot protect systems that are probabilistic, adaptive, and deeply embedded into business workflows.
As organizations deploy GenAI and agentic systems at scale, risk increasingly emerges from how AI behaves, what it connects to, and how attackers can manipulate those interactions. Mindgard addresses this challenge with an attacker-aligned approach that mirrors how real adversaries perform reconnaissance, map attack surfaces, exploit system behavior, and pivot through tools, data, and infrastructure. Rather than testing models in isolation, Mindgard evaluates full AI systems in context to surface vulnerabilities with real security impact.
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