End-to-end protection Creates a security loop from input to output. This feature addresses key challenges for large models in business scenarios, such as content security, external attacks, privacy leaks, and uncontrolled outputs.

Sample AI Sentinel closed-loop scenario diagram

Intelligent dual-engine Deeply integrates multimodal LLMs with a moderation large model based on Supervised Fine-Tuning (SFT). It combines adversarial detection and semantic understanding to accurately detect highly concealed threats, such as text variations, homophones, metaphorical expressions, and ideological infiltration.

Streaming moderation Provides end-to-end streaming moderation. Content is inspected in real time, segment by segment, as the model generates it. This process reduces latency from token generation to threat detection and ensures smooth, secure interactions in high-concurrency scenarios.

Long-context awareness Supports threat detection in single-turn and multi-turn Q&A scenarios. It incorporates historical conversation data to detect cross-turn induction, semantic drift, and jailbreaking behaviors. This provides an accurate understanding of the full conversational intent and prevents misjudgments caused by fragmented context.

Multimodal protection Provides detection for mixed modalities, such as text, images, and files. It effectively detects cross-modal hidden instructions and composite attacks, ensuring comprehensive multimodal threat coverage.

Flexible and fast integration Integrates easily through an All-in-One API, where a single call performs omni-modal detection. You can enable mitigation capabilities as needed for simple and efficient integration. The service is also natively integrated with platforms such as AI Gateway and WAF for one-click enablement.

Elastic performance configuration Uses algorithm orchestration to dynamically balance accuracy, latency, and cost. For high-concurrency and low-latency scenarios, it provides a high-performance service while ensuring effective detection to meet demanding production requirements.

Visualization and customization Provides a visualization console where you can configure risk policies, manage blacklists and whitelists, adjust thresholds, and validate effectiveness. You can also create custom detection agents and define custom labels and prompts to precisely detect business-specific threats in industries such as finance, healthcare, and education. This enables flexible extension and deep customization of security capabilities.