Overview
Operant AI was founded on the observation that the AI application stack introduces a class of runtime attacks that traditional WAFs and API gateways were never designed to handle. Prompt injection, model extraction, data exfiltration through LLM outputs — these require new detection logic at the inference layer, not just the network perimeter.
What They’re Building
The platform instruments AI applications, APIs, and cloud workloads at runtime — intercepting requests and responses to detect and block:
- Prompt injection and jailbreaking — adversarial inputs designed to subvert LLM behavior
- Rogue agent activity — autonomous AI taking unauthorized actions
- Data poisoning — malicious inputs intended to corrupt model outputs
- Sensitive data exfiltration — PII, credentials, or proprietary data leaking through LLM responses
Protection covers the full stack: the API gateway, the application layer, and the AI inference endpoints.
Traction
- $10M Series A (September 2024)
- Growing customer base across enterprises running AI in production
Why It Matters
Every major enterprise is deploying AI-powered applications, and most have no runtime visibility into what those systems are actually doing. Operant fills the gap between “we deployed an LLM” and “we know it’s behaving safely.”