This data sheet provides an overview of the SPLX Platform’s AI Runtime Threat Inspection capabilities – designed for CISOs, AI security teams, and engineering leads responsible for monitoring AI systems post-deployment. The platform enables organizations to detect malicious prompts, policy violations, and behavioral drift in real time – providing deep visibility into how AI systems behave while in production.

Monitor Threats in Live AI Deployments

• Continuously inspect LLM inputs and outputs in production environments

• Detect jailbreaks, unsafe outputs, prompt injections, and off-topic behavior as they happen

• Surface malicious patterns and user manipulation tactics in real-world interactions

Get Complete Visibility into Live System Behavior

• Access raw interaction logs tied to threat detection events and policy violations

• Trace the evolution of prompts and understand which actions triggered security rules

• Triage incidents with full context and support faster root-cause analysis

Detect Emerging Threats Before They Escalate

• Catch prompt-based attacks that evade static filters or prompt hardening

• Monitor behavioral drift in AI responses across use cases and business functions

• Feed runtime insights back into red teaming and policy updates

Extend your AI security coverage beyond testing. Download the data sheet to learn how SPLX helps organizations monitor and mitigate risks in near real time – securing AI systems at every stage of the AI lifecycle