CQAI is an API security platform that detects threats through behavioral fingerprinting and machine learning analysis. The system analyzes API headers and payloads using global ML models while applying local models to determine behavior and intent. It maintains a database of billions of API threat records and over 100 million IP addresses to identify malicious infrastructure. The platform provides agentless integration with network infrastructure components including API gateways, CDNs, proxies, and load balancers. It can be deployed as SaaS, in data centers, or cloud environments. CQAI creates behavioral fingerprints for each attack and tracks attackers as they modify their tactics. The system includes ML-based risk assessment rules to identify APIs leaking sensitive data and detect vulnerabilities from authentication coding errors and specification non-conformance. It offers hundreds of out-of-the-box rules that translate findings into inline prevention policies with response options including block, rate limit, geo-fence, and deception capabilities. CQAI continuously updates its ML models based on emerging threats and pushes updates to customers. The platform aims to minimize false positives while detecting sophisticated API attacks that may evade traditional security controls.