<ul><li>The process of extracting and organizing data from complex SOPs and department heads was proving to be a logistical nightmare.</li><li>The idea of using Retrieval-Augmented Generation (RAG) for this task led to the discovery of IBM's NeuralSeek.</li><li>Despite the steep learning curve, the team successfully fine-tuned the AI model and achieved incredible results.</li><li>To reduce the cost of goods sold (COGS) from 190% to 15%, a decision was made to build an in-house RAG solution.</li></ul>

Building RAG from the Ground Up: A Journey from High Costs to High Impact

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