This article explores the challenge of grounding Large Language Models (LLMs) for applications like Know Your Customer (KYC) and due diligence, highlighting their tendency to hallucinate or provide outdated information. It proposes using the Portfolio Investigate API to provide LLMs with verifiable data, such as WHOIS records, IP geolocation, and sanctions lists. This approach aims to transform LLM prototypes into trustworthy tools by anchoring their responses in factual, timestamped evidence. AI
IMPACT Enables more reliable AI-powered compliance and due diligence tools by grounding LLM outputs in verifiable data.
RANK_REASON Article describes a tool that integrates LLMs with external data sources for improved accuracy in specific applications.
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