KATAIQ

Gartner frames preemptive cybersecurity as the shift away from reactive detect-and-respond toward AI that anticipates and neutralizes threats before they materialize — built on the "3 D's": deny, deceive, disrupt. KATAIQ applies the deny principle to the LLM layer: it stops prompt attacks before they ever reach your model. The problem. Every public-facing LLM — support bots, website assistants, SaaS AI features — is exposed to prompt injection, jailbreaks, PII leakage, and toxic content. Rule-based filters and single-model classifiers miss novel attacks because they only know the patterns they were trained on. How it works. KATAIQ is a drop-in proxy with an OpenAI-compatible endpoint that sits between your application and any LLM API — no code changes. A fast PreFilter resolves 80%+ of traffic in under 10ms; anything ambiguous escalates to a parallel pipeline of specialized agents (semantic, encoding, intent, context, and indirect-injection analysis) that reason concurrently before a verdict is returned. Median full agent analysis runs in under 500ms. Key differentiators:

• Reasoning, not just rules — multi-agent analysis catches novel attacks no single rule-based or ML system detects ("thinks before it blocks").

  • Backend-agnostic — works with OpenAI, Anthropic, Ollama, Azure OpenAI, LiteLLM, and Bedrock.

  • Per-tenant configurable policies for multi-customer deployments.

  • Audit-grade telemetry — structured JSON logs and Prometheus metrics for a full reasoning trail on every decision.

Deployment. On-premises or SaaS, with a self-hosted Docker Compose option for fast, isolated rollout. KATAIQ is part of AST's preemptive security portfolio — extending the same anticipate-and-neutralize philosophy behind AST's broader Autonomous Cyber Immune System to the AI application layer. Learn more at https://www.kataiq.com/.