An Intellyx Brain Candy Brief
Auquan uses an enhanced retrieval augmented generation (RAG) process to improve the quality and applicability of conversational AI for common financial services workflows.
Auquan improves the quality of generative AI results – both summaries and chats — by improving the data and setting the appropriate context for large language models (LLMs) tailored for the workflows.
The Auquan tooling embeds the models with the data, curates the generated vector model, and maps it to an industry specific domain model for context.
The AI models are tailored for financial services workflows such as identifying sales leads, analyzing investment decisions, politically exposed person (PEP) screening, sanctions screening, environmental, social and governance (ESG) risks, and responding to lawsuits and fines.
Auquan ingests data from multiple external sources and combines it with internal data sources as input to the AI engine to generate summary reports, dashboards, and support interactive chat prompts.
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