Private LLMs

Jun 30,2026

LLM Security in 2026: Why Traditional Cybersecurity Is No Longer Enough

Large Language Models are transforming enterprise operations, but they introduce entirely new security risks. From prompt injection to data leakage, organizations need an AI-specific security strategy to deploy LLMs safely and at scale.

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Jan 23,2026

AI‑Enabled DLP: What It Must Do to Be Effective

Learn how the expansion of data loss prevention (DLP) into AI‑aware controls addresses real enterprise risks, secures sensitive data in AI environments, and enables responsible AI adoption with modern governance and inspection techniques. In the last two years, the acceleration of generative AI usage has produced dramatic increases in sensitive…

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Oct 17,2025

OWASP Top 10 AI Security Risks: What Every Enterprise Should Know

Discover the OWASP (Open Worldwide Application Security Project)Top 10 AI Security Risks, from data leakage and model manipulation to AI supply chain vulnerabilities. Learn what these mean for enterprises adopting AI and how to strengthen governance, compliance, and resilience with private AI strategies. AI is no longer experimental, it’s embedded…

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Oct 08,2025

Keeping Your Business Safe AI Routing and Pragatix

No single AI model can handle everything. As a result, enterprises often end up running multiple AI models at once, a setup often described as multi-AI environments. This approach delivers efficiency and flexibility but also introduces new risks: data leakage, compliance failures, and uncontrolled employee use of public AI tools…

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Oct 02,2025

Five Critical AI Risks Facing Enterprises in 2025

With rapid adoption comes a growing set of risks that can’t be ignored. For enterprises, overlooking these risks doesn’t just mean inefficiency; it means legal exposure, financial penalties, and long-term reputational damage. This blog explores the top 5 AI risks enterprises must monitor, and how Pragatix delivers the governance, security,…

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