Confidently deploy safe, secure, and trustworthy generative AI systems with guardrails

An out-of-the-box guardrail framework accelerates deployment

It saves time by providing pre-built safety protocols, allowing teams to focus on core functions and speeding up deployment

Cuts deployment costs by up to 30% by reducing custom development and setup time by 40%, while ensuring compliance to decrease regulatory expenses by 20%.

Our framework eliminates implementation risks with automated compliance and reliable security measures.

Our framework delivers swift, measurable business value by streamlining processes and ensuring compliance, boosting productivity and ROI.

Open standard guardrail controls for business functions across industries

Guardrail controls ensure all content types are compliant and accurate, aligning with brand standards and boosting trust.

Our guardrail controls ensure words and phrases are compliant and brand-aligned, maintaining consistency across communications.

Our guardrail controls protect sensitive information by ensuring compliance and preventing unauthorized access, safeguarding data integrity and privacy.

Our solutions ensure data privacy by implementing robust security measures, protecting sensitive information and maintaining user trust.

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How do guardrails function in enterprise landscapes: small, medium, and large?

Guardrails monitor for policy violations in real-time, triggering automated responses to block unauthorized actions. They enforce compliance by immediately halting activities that breach security or operational standards. This proactive approach minimizes risks and maintains system integrity.

Our Guardrails can automatically detect and mask sensitive information, ensuring data privacy. They apply encryption and anonymization techniques to protect personal and confidential data, preventing unauthorized access and maintaining compliance.

Guardrails serve as a centralized control system between users, LLMs, and data sources by managing access and ensuring compliance across interactions. They oversee data exchanges, enforce security measures, and maintain consistent standards, facilitating seamless and secure communication among all components.

Guardrails Control Matrix: Qualitative and Quantitative

Our Guardrails Control Matrix defines risk levels—low, medium, and high—and outlines specific threshold limits. These qualitative assessments guide our responses to ensure compliance. By categorizing risks, we tailor strategies for effective governance and risk management.

Our Quantitative Guardrails Matrix uses data-driven metrics to assess risks and performance. By setting numerical thresholds, we can precisely monitor and manage compliance. This approach ensures informed decision-making and efficient resource allocation.

Our threshold limits define the point at which an action is triggered to maintain compliance and safety. These limits ensure timely responses to potential risks, preventing violations before they escalate. By setting precise thresholds, we enhance control and decision-making effectiveness.

We are the market leader in deploying
enterprise-grade guardrail systems

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End-to-end guardrail workflow to build stakeholder trust and stay in compliance

Our guardrails gain stakeholder trust by ensuring consistent compliance and security across operations. They provide transparency through real-time monitoring and reporting. This reliability fosters confidence and strengthens relationships with stakeholders.

Our guardrails ensure compliance by automating enforcement and real-time monitoring, quickly addressing violations and safeguarding reputations.

Types of guardrails

Compliance guardrails ensure that business operations adhere to industry regulations and standards. They automate policy enforcement, reducing the risk of violations and penalties. By providing real-time monitoring and reporting, they maintain organizational integrity and build stakeholder trust.

Safety guardrails are designed to protect personnel and assets by preventing accidents and hazards. They provide physical and procedural barriers, ensuring a secure operational environment. Through continuous monitoring and alerts, they help maintain a culture of safety and compliance across the organization.

Domain-specific guardrails are tailored to meet the unique requirements of particular industries or sectors. They integrate specialized compliance and operational standards, ensuring adherence to relevant regulations. By addressing industry-specific risks, they enhance efficiency and security within the targeted domain.
Guardrail Type Purpose Key Features Government Use Case
Content Guardrails Ensures outputs are professional, relevant, and free from toxicity. Content filtering, tone calibration, topic restriction. A chatbot restricts discussions to public service topics while blocking offensive language.
Safety Guardrails Prevents misinformation, hallucinations, and unsafe outputs. Prompt validation, output verification, operational safety. A disaster response system validates evacuation plans for accuracy and compliance with protocols.
Compliance Guardrails Ensures adherence to legal, regulatory, and privacy standards. PII redaction, policy enforcement, access control. A taxation assistant ensures responses comply with privacy laws like CCPA and GDPR.
Bias Mitigation Guardrails Promotes fairness and inclusivity by addressing bias in outputs. Bias detection, fairness algorithms, performance monitoring. A resource allocation system corrects biases to ensure fair distribution of housing resources across diverse communities.
Domain-Specific Guardrails Tailors AI outputs to meet the unique requirements of specific industries or functions. Contextual validation, custom policies, multi-agent collaboration. A healthcare AI assistant validates medical recommendations against approved clinical guidelines, ensuring alignment with government healthcare policies.

What types of data can guardrails work with?

Data Type Challenges Addressed Guardrail Solutions Government Use Case
Text PII leakage, toxic outputs, off-topic responses PII redaction, content filtering, compliance validation Taxation assistant ensuring accurate and secure citizen communication.
Numerical/Tabular Inaccuracies, bias, data leakage Accuracy validation, bias detection, encryption Budget planning tool validating fiscal allocations.
Image Misinterpretation, sensitive data exposure Content moderation, privacy safeguards, contextual validation Disaster management analyzing flood imagery while protecting sensitive information.
Audio Toxic language, privacy violations, miscommunication Tone moderation, PII filtering, content filtering Emergency hotline AI providing empathetic and accurate responses.
Multimodal Data misalignment, privacy risks, inaccuracies Cross-validation, PII redaction, accuracy verification Telehealth AI ensuring consistency between audio consultations and text-based treatment summaries.

Our guardrails manage multimodal data by integrating and securing diverse data types, such as text, images, and audio. They ensure consistent compliance across all formats, enhancing data integrity and reliability. This comprehensive approach allows for seamless data processing and analysis, optimizing outcomes.

Our guardrails tackle data challenges by securing diverse data types, ensuring compliance and integrity. They provide automated monitoring and protection, handling everything from structured to unstructured data. This approach ensures reliable and efficient data management across all formats.

Building guardrail business cases for LLM-based applications in public services

Our framework supports building business cases for government services by aligning projects with public objectives and demonstrating value. It assesses impact, cost-effectiveness, and ensures regulatory compliance. This approach secures stakeholder support and funding for successful implementation.

Developing guardrail business cases for public-facing applications with our framework involves identifying key risks and compliance needs. It assesses impact, ensures data security, and enhances user trust. By aligning with stakeholders' goals, it secures support and funding effectively.

Guidelines for Establishing Advanced
Guardrail Systems in Enterprises

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A step-by-step approach to implementing enterprise-grade guardrail controls

From Data Preparation to Training, and then Deployment

Step 1: Setting Up Your Project Environment

  • Purpose: Establish a secure and organized foundation for smooth development and deployment.
  • Objective: Set up a structured directory, install required libraries, and configure secure environment variables.
  • Action:
    • Create the project directory structure (e.g., src/, image/, style/).
    • Install dependencies (pip install -r requirements.txt).
    • Set up the .env file to securely store API keys and environment variables.
    • Build the Docker container using the Dockerfile.

Step 2: Setting Up the Main Application in app.py

  • Purpose: Develop a user interface for seamless execution of multimodal functionalities.
  • Objective: Create a robust Python application that integrates various components.
  • Action:
    • Write the main application script in app.py.
    • Import and call modules like main.py to execute core workflows.
    • Use logging and structured layouts for easy debugging and navigation.

Step 3: Implementing Guardrails AI in guardrails_ai.py

  • Purpose: Enable safe and validated AI workflows by integrating guardrails.
  • Objective: Ensure AI responses align with defined rules and validations.
  • Action:
    • Implement guardrail-specific rules for processing AI outputs.
    • Validate and refine AI outputs using the guardrails_ai.py module.

Step 4: Implementing OpenAI Integration in guardrails_openai.py

  • Purpose: Enable interaction with OpenAI APIs for text and multimodal input processing.
  • Objective: Process multimodal data using OpenAI’s GPT models.
  • Action:
    • Write the interaction logic in guardrails_openai.py.
    • Pass user queries (text, image metadata) to OpenAI APIs and retrieve responses.
Assessment
and
Planning
Integration
and
Testing
Training
and
Monitoring

Step 5: Implementing NVIDIA Guardrails in guardrails_Nvidia.py

  • Purpose: Enhance multimodal workflows using NVIDIA’s Guardrails and tools.
  • Objective: Use NVIDIA’s libraries for robust multimodal data handling and AI optimization.
  • Action:
    • Implement NVIDIA guardrails functionalities using guardrails_Nvidia.py.
    • Configure NVIDIA-specific parameters in config.yml and prompts.yml.

Step 6: Core Workflow Management in main.py

  • Purpose: Centralize the application workflow for efficient execution.
  • Objective: Manage data flow between input, processing, and output stages.
  • Action:
    • Implement the core logic in main.py.
    • Call modules like guardrails_ai.py and utilities.py to process input and generate output.
    • Use logging to monitor the workflow.

Step 7: Utility Functions in utilities.py

  • Purpose: Streamline code efficiency by handling repetitive tasks.
  • Objective: Develop reusable functions for data formatting, file handling, and logging.
  • Action:
    • Write helper functions in utilities.py.
    • Use utilities for file handling, data organization, and preprocessing tasks.

Step 8: Running the Application

  • Purpose: Integrate all modules for a functional and seamless experience.
  • Objective: Test and optimize the application for smooth execution.
  • Action:
    • Run the app.py file to start the application.
    • Test multimodal features (text, image, video).
    • Debug and optimize as needed to enhance performance and usability.