RagaAI launches open source LLM hub to facilitate language model evaluation and safety
Posted: March 8, 2024 5:12 AM Updated: March 8, 2024 5:22 AM
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RagaAI has launched ‘RagaAI LLM Hub’, an open source platform for evaluating and building 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 to evaluate and set guardrails for large language models (LLMs). With over 100 meticulously crafted metrics, this platform aims to prevent catastrophic errors in LLM and Retrieval Augmented Generation (RAG) applications.
RagaAI LLM Hub provides developers and organizations with a powerful toolkit to effectively evaluate and compare LLMs, covering critical aspects such as relevance and comprehension, content quality, hallucinations, safety and bias, contextual relevance, guardrails and vulnerability scanning. We also offer a metric-based test suite for quantitative analysis.
“A holistic evaluation of LLMs is a key requirement in the current world of LLM deployments, as data scientists and companies figure out which technologies and stacks are right for them. Diagnosing a problem requires meticulous identification of the problem at the source, and when there are hundreds of possible root causes, you need hundreds of metrics to pinpoint those root causes,” Gaurav Agarwal, founder of RagaAI, told MPost.
“RagaAI LLM Hub’s comprehensive testing capabilities add significant value to developers’ workflows, saving critical time by eliminating ad hoc analysis and accelerating LLM development by 3x.”
Designed to solve problems across the LLM lifecycle, from proof of concept to production applications, RagaAI LLM Hub innovates the approach to ensure trustworthiness and trustworthiness by identifying fundamental issues within LLM applications and facilitating resolution at the source.
RagaAI claims that LLM Hub augments this functionality with a variety of tests covering different aspects of decision-making.
- Prompts: Iterate and identify optimal prompt templates while establishing guardrails to mitigate adversary attacks.
- Context Management for RAG: Helps users find the optimal balance between LLM performance and cost/latency when operating at scale.
- Response Generation: Use metrics to identify hallucinations in LLM responses and set guardrails to prevent bias, PII leaks, and other potential issues.
Mitigating AI hallucinations and bias through LLM diagnostics
RagaAI LLM Hub supports developers and enterprises in tasks such as chatbots, content creation, text summarization, and source code generation, finding applications in a variety of industries including e-commerce, finance, marketing, law, and healthcare.
In addition to assessments, RagaAI LLM Hub supports setting guardrails to ensure data privacy and legal compliance, and promotes ethical and responsible AI practices, especially in sensitive sectors such as finance, healthcare, and law.
“One of our e-commerce customers was using LLM for a chatbot for customer support, and the chatbot was giving incorrect answers. With RagaAI, this issue was successfully detected and resolved,” RagaAI’s Gaurav Agarwal told MPost. “In health insurance, it is important to keep patients’ personal information safe. For one of our customers, some of their sensitive personal information was shared with third parties, creating a huge data privacy issue. We used RagaAI LLM Hub guardrails to detect and prevent this and other similar issues from occurring in real time.”
We also aim to mitigate reputational risk by adhering to social norms and values.
“RagaAI helps establish guardrails such as personally identifiable information (PII) detection in our LLM response. This ensures that personal data in internal documents is not leaked by the LLM application and is critical for Responsible AI,” explained Gaurav Agarwal. “These and other measures, such as ensuring a fair and impartial response, prohibiting comments about competitors, and removing material non-public information (MNPI), are critical for businesses seeking to avoid social and reputational harm.”
The launch of RagaAI LLM Hub follows the successful raising of $4.7 million in a January 2024 seed funding round led by pi Ventures to expand AI research, development and customer base across the U.S. and Europe.
“Our goal is to provide the best technology to make LLM trustworthy and trustworthy. We are making significant investments to build core technologies to address quality assurance aspects of the LLM. Making this technology open source is our effort to make this technology available to everyone so that the developer community can build on the best solutions,” said Gaurav Agarwal.
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Victor is the Managing Technology Editor/Writer at Metaverse Post and covers artificial intelligence, cryptography, data science, metaverse, and cybersecurity within the enterprise space. He boasts of five years of media and AI experience working at renowned media outlets such as VentureBeat, DatatechVibe, and Analytics India Magazine. Having worked as a media mentor at prestigious universities such as Oxford and USC, and holding a Master’s degree in Data Science and Analytics, Victor is committed to keeping up with new trends. He provides readers with the latest and most insightful stories from the world of technology and Web3.
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victor day
Victor is the Managing Technology Editor/Writer at Metaverse Post and covers artificial intelligence, cryptography, data science, metaverse, and cybersecurity within the enterprise space. He boasts of five years of media and AI experience working at renowned media outlets such as VentureBeat, DatatechVibe, and Analytics India Magazine. Having worked as a media mentor at prestigious universities such as Oxford and USC, and holding a Master’s degree in Data Science and Analytics, Victor is committed to keeping up with new trends. He provides readers with the latest and most insightful stories from the world of technology and Web3.