Aiceberg Risk Signals Library vs Oligo Runtime AI: Side-by-Side Comparison (2026)

Aiceberg Risk Signals Library

Mid-market and enterprise security teams deploying generative AI applications need Aiceberg Risk Signals Library to catch prompt injection and data exfiltration before they happen, which most traditional DLP tools completely miss. The library's dual focus on input validation (prompt injection detection) and output controls (prompt leaking prevention) covers the attack surface unique to LLM applications, addressing gaps in PR.DS and DE.CM that legacy platforms ignore. Skip this if your GenAI use is experimental or limited to public ChatGPT; the pricing and operational overhead make sense only when AI models are handling sensitive data at scale.

Oligo Runtime AI

Enterprise security teams protecting agentic AI deployments need Oligo Runtime AI because it's built explicitly for detecting hijacked agents and model exfiltration, not bolted onto a generic runtime platform. The tool covers five NIST CSF 2.0 functions with particular strength in continuous monitoring and adverse event analysis, catching unsafe model configurations and untrusted components in real time. Skip this if you're still operating with static AI inventories or if you lack the AppSec bandwidth to manage security guardrails; Oligo assumes mature AI governance practices already exist.