Guardrails the safety layer built into every agent run

Guardrails intercepts every LLM input and output at the runtime layer scanning for prompt injection, PII, toxicity, and semantic policy violations before execution continues. Not a wrapper. Not optional. A first-class runtime primitive in every elsai workflow.

Get started →

Talk to an architect →

Enterprise-grade AI safety

Comprehensive guardrails to protect your AI applications from security threats,

compliance violations, and quality issues.

Comprehensive guardrails to protect your AI applications from security threats,

compliance violations, and quality issues.

Toxicity detection

Automatically identify and filter harmful, offensive, or inappropriate content in AI responses before they reach your users.

Hallucination detection

Detect when AI generates false or misleading information not grounded in factual data or provided context.

PHI/PII detection

Protect sensitive personal health information and personally identifiable information from being exposed or processed.

Sensitive data detection

Identify and redact financial data, credentials, API keys, and other sensitive information in AI interactions.

Jailbreak detection

Prevent attempts to bypass AI safety measures and manipulate your models into generating harmful outputs.

Prompt injection

Block malicious prompts designed to hijack your AI system's behavior or extract sensitive information.

Production-ready validators

Deploy enterprise-grade AI validation in minutes. Our validators are battletested, highly performant, and designed for scale.

Real-time validation with sub-100ms latency

Easy API integration with any LLM provider

Comprehensive logging and analytics

Customizable thresholds and rules

SOC2 compliant infrastructure

Book a live agent demo →

guardrails.py

from elsai_guardrails.guardrails import LLMRails, RailsConfig

yaml_content = """

llm:

engine: "openai"

model: "gpt-4o-mini"

api_key: "sk-..."

guardrails:

input_checks: true

check_toxicity: true

check_sensitive_data: true

check_semantic: true

"""

config = RailsConfig.from_content(yaml_content=yaml_content)

rails = LLMRails(config=config)

# Input will be automatically checked

result = rails.generate(

messages=[{"role": "user", "content": "user input"}],

return_details=True

)

if result.get('input_check'):

print(f"Input passed: {result['input_check'].passed}")

More validators on the way

We're constantly expanding our guardrail capabilities. Stay tuned for these

upcoming features.

We're constantly expanding our guardrail capabilities. Stay tuned for these

upcoming features.

Coming Soon

Off-Topic Detection

Automatically detect when conversations drift from

intended topics and keep your AI focused on relevant

discussions.

Automatically detect when conversations drift from intended topics and keep your AI focused on relevant discussions.

Coming Soon

Valid SQL Validation

Ensure AI-generated SQL queries are syntactically correct

and safe before execution, preventing database errors

and injection attacks.

Ensure AI-generated SQL queries are syntactically correct and safe before execution, preventing database errors and injection attacks.

Ready to secure your AI?

We're constantly expanding our guardrail capabilities. Stay tuned for these upcoming features.

Start free trial →

elsai

Enterprise AI governance platform for agentic workflows. Transform your operations with confidence.

Platform

Guardrails

AI observability

Prompt manager

Resources

Documentation

Case studies

Blog

Company

About

Careers

Contact

Partners

Privacy

Terms