Embed safety, compliance, and policy enforcement at the core of every AI workflow — built for production from day one.
Get StartedEnterprise-grade guardrails that validate every LLM interaction in real time — without sacrificing speed, flexibility, or control.
Low-latency protection wraps your LLM application to catch PII leaks, hallucinations, jailbreaks, and any custom policy — before output reaches users.
65+ pre-built validators covering hallucination, PII, jailbreaks, and content moderation — deploy out of the box or extend with your own.
OpenAI, Anthropic, Meta, or custom models. Cloud or on-prem. Chatbots, RAG pipelines, and autonomous agent workflows.
Oloyid sits at the center of your AI stack — validating traffic from any application before it reaches any model provider.
Guardrails are a safety layer between users and large language models. They inspect every input and output before it reaches your users or downstream systems — enforcing rules, validating formats, and automatically correcting or blocking unsafe responses.
Without guardrails, LLMs can hallucinate facts, leak sensitive data, produce toxic content, or return unstructured outputs that break your application. Oloyid solves this as a composable, open source framework you fully control.
Six core validation domains — composable, production-tested, and ready to deploy across any LLM workflow in your stack.
Detect and mask names, emails, SSNs, and phone numbers before sensitive data leaves your system.
Guarantee valid JSON and schema compliance with automatic retry and corrective re-prompting on failure.
Block jailbreak attempts, adversarial prompts, and instruction-override attacks before they reach your model.
Filter toxic language, hate speech, bias, and off-brand content to keep AI responses professional.
Validate factual consistency against source documents and catch fabricated claims in real time.
Mix pre-built validators from the hub or write your own in Python — add a new safety check in one line.
65+ validators · Apache 2.0# Install Oloyid pip install oloyid # Define a guard and wrap your LLM call from oloyid import Guard from oloyid.hub import DetectPII, ValidJSON guard = Guard().use( DetectPII(on_fail="fix"), ValidJSON(schema=MySchema) ) response = guard( llm_api=openai.chat.completions.create, prompt="Summarize this customer ticket..." )
Production-ready AI guardrails
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