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Benchmarking Against Industry Leaders with Alinia RAG Guardrails

Alinia RAG Guardrails set a new standard in detecting hallucinations and irrelevance in Retrieval-Augmented Generation (RAG) applications. Our benchmarks demonstrate industry-leading performance across multiple languages, short-context scenarios, as well as domain-specific scenarios on public and high quality proprietary datasets. With significant improvements in detecting irrelevant responses and RAG-retrieved contexts, Alinia RAG Guardrails are the go-to

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Hallucination Detection Redefined

Our Alinia RAG Guard is a leading model for detecting hallucinations and irrelevance in RAG-based applications. Tested across six languages and benchmarked against industry leaders like GPT-4o-mini, IBM Granite, and AWS Bedrock, our multilingual guardrails deliver up to 40% better performance in reducing errors—especially in high-stakes domains like finance and healthcare. Built for trust, speed, and precision, Alinia RAG Guard empowers enterprises to deploy reliable, regulation-ready AI assistants at scale.

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