LLM Guardrails: How Prompteus Helps Regulated Industries Safely Leverage AI

As organizations in regulated sectors like healthcare, finance, and public services are trying to find more efficient ways of working and increasingly integrate generative AI into their software, ensuring responsible and compliant AI behavior becomes paramount.

Learn about how Prompteus can help you rule AI, by setting a layer of guardrails between LLMs and your user interface, reducing risks and allowing you to stay compliant and on brand.

AI risks

AI is flawed. This can lead to different consequences for organizations that rely on AI in their processes.

• Answers from AI models can be biased, unfair, or even inaccurate (totally invented, ie. hallucinations) and it can seriously damage a business reputation if left unsupervised while interacting with users.

• Compliance is also a major concern with AI as it can hallucinate or create approximate outputs that do not respect internal or external regulations, exposing organizations to complaints, reputation damage, or even legal action—or even potential real-life health consequences in Healthcare.

• A LLM can inadvertently disclose personal information if not trained specifically for this use case, representing a major limitation in its uses and a major risk for organizations that do not specify rules on top of AI models or omit certain guardrails during implementation. 

• Ill intended actors can manipulate AI-powered agents into producing incorrect outputs or trick them into revealing restricted information or bypass security measures, potentially leading to security vulnerabilities or data breaches.

Understanding LLM Guardrails

LLM guardrails are built-in safety rules that guide how large language models behave in real-world applications. Introduced as part of LLM Operations, they help ensure AI systems remain ethical, secure, and aligned with business goals.

These guardrails play a crucial role in managing risk—preventing harmful outputs, enhancing context awareness, and ensuring AI responses stay within acceptable and legal boundaries. As generative AI becomes more deeply embedded in digital products, guardrails are essential for maintaining trust and driving responsible innovation.

Prompteus Neurons: Building AI Guardrails Without Code

Prompteus provides a no-code environment where users can build AI workflows using modular components called  "neurons." These neurons can be configured to enforce various safety and compliance measures, ensuring that AI outputs align with organizational policies and regulatory requirements.

Set System Instructions

• Purpose: Allows you to define or modify the System Instructions for a Neuron.

• Use Case: Enforce a specific answer structure for healthcare responses to ensure they comply with HIPAA regulations.

• Example: A hospital uses Prompteus to ensure that all medical advice includes a disclaimer: "This information is not a substitute for professional medical advice."

Replace Words in Prompt

• Purpose: Replace specific words or regular expressions in the prompt with other defined words.

• Use Case: Replace user-entered "SSN" with "Social Security Number" for consistent language processing.

• Example: A financial service uses Prompteus to ensure all user inputs are transformed to match compliance language, preventing vague references to personal information.

Replace Words in Response

• Purpose: Replace specific words or regular expressions in the LLM response with other defined words.

• Use Case: Mask sensitive information like client names in responses to avoid privacy breaches.

• Example: A law firm uses Prompteus to ensure AI never discloses client names in legal document reviews.

If Input Contains

• Purpose: Analyzes user inputs for potentially harmful or non-compliant content before processing.

• Use Case: Prevents prompt injection attacks or the submission of inappropriate queries.

• Example: If a user input includes the command "ignore previous instructions," the system can reject the input to maintain prompt integrity.

If Output Contains

• Purpose: Monitors LLM outputs for specific keywords or patterns.

• Use Case: Detects and prevents the dissemination of sensitive information, such as personally identifiable information (PII) or prohibited content.

• Example: If an output contains the phrase "social security number," the workflow can be configured to block the response or trigger an alert.

Additional capabilities 

• Use Regex to identify complex patterns in inputs or outputs and enforce strict formatting or content rules, such as validating email addresses or detecting credit card numbers, to adhere to regulatory standards.

• Comprehensive Observability and Logging: Prompteus logs every AI request and response, providing a transparent audit trail. This level of detailed monitoring is essential for demonstrating adherence to regulations such as HIPAA in healthcare and various financial compliance standards.

Why Prompteus Is Ideal for Regulated Industries

• Compliance Assurance: Enables organizations to enforce industry-specific regulations and internal policies directly within AI workflows.

• Risk Mitigation: Provides tools to prevent the release of unauthorized or harmful information, safeguarding both the organization and its clients.

• Operational Efficiency: Streamlines the development and deployment of AI solutions without the need for extensive coding, reducing time-to-market.

• Auditability: Maintains detailed logs of AI interactions, facilitating audits and reviews to ensure ongoing compliance.

Prompteus empowers organizations in regulated industries to enhance their compliance frameworks, protect sensitive information, and maintain the trust of those they serve.

By leveraging Prompteus's suite of nodes and its intuitive workflow builder, organizations can confidently integrate AI into their operations, knowing that robust guardrails are in place to ensure safety, compliance, and reliability.

By supporting multiple large language models, Prompteus also ensures that organizations are not dependent on a single AI provider. This flexibility boosts cost-efficiency allowing guardrails to be applied at large across models, but allows for adjustments based on evolving regulatory guidelines, ensuring sustained compliance.