Secure LLM and SLM Integrations
AI guardrails are a set of controls designed to ensure safe and secure AI interactions. Positioned between your LLM or SLM and the user interface, Prompt uses these guardrails to intercept, block, and mitigate risks to generative AI applications in real-time, addressing issues such as prompt injections, jailbreaks, and data leakage.
The primary purpose of Prompt is to maintain the reliability of your AI application. Without these safeguards, prompts created for an LLM or SLM application may lead to unintended behavior, as AI is prone to errors and can be easily manipulated by hackers and savvy users.
Safeguard Your Generative AI Applications
Detect
Scan AI prompts for adversarial inputs, PII, or other sensitive data in real-time.
Protect
Block or de-identify data in detected prompts depending on policy configurations.
Validate
Prevent toxic or bias statements and re-identify sensitive data in AI responses.
Control Your Data
Automate prompt and response filtering
- Built-in defense against prompt injection threats, data leakage, jailbreaks, gibberish, and other harmful inputs
- De-identify prompts containing sensitive data before sending to LLMs and re-identify upon return to preserve full context and privacy
- Evaluate and block responses containing bias, toxicity, and other unethical or inappropriate statements
Real-Time Mitigation
Automate prompt and response filtering
- Built-in defense against prompt injection threats, data leakage, jailbreaks, gibberish, and other harmful inputs
- De-identify prompts containing sensitive data before sending to LLMs and re-identify upon return to preserve full context and privacy
- Evaluate and block responses containing bias, toxicity, and other unethical or inappropriate statements
Model Agnostic
Use with any generative AI model or application
- Built-in defense against prompt injection threats, data leakage, jailbreaks, gibberish, and other harmful inputs
- De-identify prompts containing sensitive data before sending to LLMs and re-identify upon return to preserve full context and privacy
- Evaluate and block responses containing bias, toxicity, and other unethical or inappropriate statements