RagaAI, is expanding its testing platform by launching “RagaAI LLM Hub“, its open-source and enterprise-ready LLMs evaluation and guardrails platform. With over 100 meticulously designed metrics, it is the most comprehensive platform that allows developers and organisations to evaluate and compare LLMs effectively and establish essential guardrails for LLMs and Retrieval Augmented Generation (RAG) applications.
These tests assess various aspects including Relevance & Understanding, Content Quality, Hallucination, Safety & Bias, Context Relevance, Guardrails, and Vulnerability scanning, along with a suite of Metric-Based Tests for quantitative analysis. The RagaAI LLM Hub is uniquely designed to help teams identify issues and fix them throughout the LLM lifecycle, be it a proof-of-concept or an application in production. From
understanding the quality of datasets to prompt templating and the choice of LLM architecture or vectorDBs, RagaAI LLM Hub identifies issues across the entire RAG pipeline.
This is pivotal for understanding the root cause of failures within an LLM application and addressing them at their source, revolutionising the approach to ensuring reliability and trustworthiness. At RagaAI, our mission is to empower developers and enterprises with the tools they need to build robust and responsible LLMs, said Gaurav Agarwal, Founder and CEO of RagaAI. With our comprehensive open-source evaluation suite, we believe in democratising AI innovation. Together with the enterprise-ready version, we’ve created a comprehensive solution to enable organisations to navigate the complexities of LLMs deployment with confidence. This is a game-changing solution that provides unparalleled insights into the reliability and trustworthiness of LLMs and RAG applications.
The RagaAI Platform is already being utilised across industries like E-commerce, Finance, Marketing, Legal, and Healthcare, and the RagaAI LLMs Hub supports developers and enterprises in various LLM applications including chatbots, content creation, text summarisation, and source code generation. For instance, one may encounter hallucinations and incorrect outputs whilst developing a customer service chatbot, leveraging
RagaAI LLM Hub's comprehensive metrics, can pinpoint and quantify the hallucination issue in the RAG pipeline. Additionally, the platform adeptly identifies nuanced customer issues and recommends specific areas within the pipeline for resolution.
The RagaAI LLM Hub helps in setting guardrails, ensuring data privacy and legal compliance, including transparency regulations and anti-discrimination laws. It plays a vital role in promoting ethical responsible AI practices, such as in sensitive sectors like finance, healthcare, and law. Additionally, it helps mitigate reputational risks by adhering to societal norms and values.