End-to-end AI security platform for evaluating, testing, and protecting large language models (LLMs) and AI systems in production. HydroX AI focuses on preventing prompt injection attacks, jailbreaks, and unsafe AI outputs through red-teaming, adversarial testing, and runtime protection. EVALUATION & TESTING Red-team LLMs with adversarial attacks to identify failure modes and weaknesses before deployment. Stress testing uncovers vulnerability to prompt injection and model manipulation. Establishes security benchmarks and measurable robustness standards. AI-DRIVEN SCRAPER Red-teaming tool that tests anti-scraping defenses using 60+ residential proxy IP addresses and AI agents that simulate human behavior. Uses LLM-based parsing instead of traditional regex to adapt to dynamic page structures. SAFETY ALIGNMENT Structured evaluation framework to ensure AI outputs align with organizational values, policies, and compliance requirements. Detects biased, harmful, or misleading outputs. Incorporates legal and ethical considerations into guardrail definition. PROTECTION Enterprise firewall and encryption for AI systems with real-time monitoring. Detects and blocks jailbreaks and prompt injection attacks. Sub-second threat detection across 30+ threat categories (toxicity, bias, data exposure, adversarial risks). Monitors encrypted runtime execution. HydroX positions as a specialized security vendor for LLM applications rather than general cybersecurity. The offering acknowledges that traditional security tools are insufficient for AI-specific attack vectors. Revenue model likely per-model-per-month or usage-based. Target market is enterprises deploying LLMs in production who need guardrails beyond base model safety training.