RagaAI Launches Open-Source LLM Hub to Ease Language Model Evaluation & Safety
In Brief
RagaAI launched ‘RagaAI LLM Hub,’ an open-source platform for evaluating and establishing guardrails for AI specific language models.
AI testing platform RagaAI recently announced the launch of “RagaAI LLM Hub,” an open-source and enterprise-ready platform designed for evaluating and establishing guardrails for Large Language Models (LLMs). With over 100 meticulously crafted metrics, the platform aims to prevent catastrophic failures in LLMs and Retrieval Augmented Generation (RAG) applications.
The RagaAI LLM Hub offers developers and organizations a robust toolkit to assess and compare LLMs effectively, covering critical aspects such as Relevance & Understanding, Content Quality, Hallucination, Safety & Bias, Context Relevance, Guardrails and Vulnerability scanning. Additionally, it provides a suite of Metric-Based Tests for quantitative analysis.
“Holistic evaluation of LLMs is a key requirement in the world of LLM building right now, as data scientists and enterprises figure out what technology and stack works for them. Diagnosing a problem requires meticulously identifying the problem at source, and given hundreds of possible root causes, it requires hundreds of metrics to pinpoint that root cause,” Gaurav Agarwal, founder at RagaAI told MPost.
“RagaAI LLM Hub’s ability for comprehensive testing adds significant value to a developer’s workflow, saving crucial time by eliminating ad hoc analysis and accelerating LLM development by 3x.”
Designed to address issues throughout the LLM lifecycle, from proof-of-concept to production applications, the RagaAI LLM Hub identifies underlying problems within LLM applications and facilitates their resolution at the source, revolutionizing approaches to ensuring reliability and trustworthiness.
RagaAI asserts its LLM Hub empowers this capability through a range of tests covering various decision-making aspects:
- Prompts: It iterates and identifies optimal prompt templates while establishing guardrails to mitigate adversarial attacks.
- Context Management for RAGs: It assists users in finding the optimal balance between LLM performance and cost/latency when operating at scale.
- Response Generation: It employs metrics to identify hallucinations in LLM responses and establishes guardrails to prevent bias, PII leakage, and other potential issues.
Mitigating AI Hallucinations and Bias Through LLM Diagnosis
The RagaAI LLM Hub finds applications across various industries, including e-commerce, finance, marketing, legal and healthcare, supporting developers and enterprises in tasks such as chatbots, content creation, text summarization, and source code generation.
Beyond evaluation, the RagaAI LLM Hub aids in setting guardrails to ensure data privacy and legal compliance, promoting ethical and responsible AI practices, particularly in sensitive sectors like finance, healthcare, and law.
“One of our customers in the e-commerce space was using LLMs for chatbot for customer support, and the chatbot was giving wrong answers. Using RagaAI, this issue was successfully detected and resolved,” RagaAI’s Gaurav Agarwal told MPost. “In health insurance, patient’s personal information is important to be safeguarded. In one of our customers, some of the important personal information was shared to the 3rd party — a huge data privacy issue. Using RagaAI LLM Hub guardrails, this and similar other issues were detected in real time and prevented from happening.”
Additionally, it aims to mitigates reputational risks by adhering to societal norms and values.
“RagaAI helps in setting guardrails like detection of Personally identifiable Information (PII) in LLM response. This ensures no personal data from internal documents is ever leaked by the LLM application and is critical to Responsible AI,” explained Gaurav Agarwal. “This and other guardrails such as ensuring unbiased and fair responses, not commenting on competitors and removing Material Non Public Information (MNPI) are crucial for firms as they look to avoid societal and reputational harm.”
The launch of the RagaAI LLM Hub follows a successful $4.7 million in a seed funding round in January 2024 led by pi Ventures, to expand its AI research, development and client base across the US and Europe.
“Our goal is to provide the best technology to make LLMs trustworthy and reliable. It is investing significantly to build key technologies to address LLM quality assurance aspects. Making this technology open-source is our effort in the direction to make this available to everyone for the developer community to build on top of best available solution,” said Gaurav Agarwal.
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About The Author
Victor is a Managing Tech Editor/Writer at Metaverse Post and covers artificial intelligence, crypto, data science, metaverse and cybersecurity within the enterprise realm. He boasts half a decade of media and AI experience working at well-known media outlets such as VentureBeat, DatatechVibe and Analytics India Magazine. Being a Media Mentor at prestigious universities including the Oxford and USC and with a Master's degree in data science and analytics, Victor is deeply committed to staying abreast of emerging trends. He offers readers the latest and most insightful narratives from the Tech and Web3 landscape.
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Victor is a Managing Tech Editor/Writer at Metaverse Post and covers artificial intelligence, crypto, data science, metaverse and cybersecurity within the enterprise realm. He boasts half a decade of media and AI experience working at well-known media outlets such as VentureBeat, DatatechVibe and Analytics India Magazine. Being a Media Mentor at prestigious universities including the Oxford and USC and with a Master's degree in data science and analytics, Victor is deeply committed to staying abreast of emerging trends. He offers readers the latest and most insightful narratives from the Tech and Web3 landscape.
