A global healthcare leader partnered with freya fusion to centralize years of Health Authority RTQ (requests/queries) interactions into a single, searchable knowledge repository. Using a blend of rule-based processing and AI/ML, historic correspondence was cleansed and enriched, while a new operating process continuously ingests future agency interactions. Teams can now discover similar prior queries, chat with the RTQ corpus, and run analytics to accelerate high-quality responses and decision-making. Download the full case study to explore the data model, ingestion & enrichment approach, search/chat experience, and measurable business outcomes.
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