How Anima Health scaled clinical document intelligence with Qdrant

Anima Health has developed a clinical operating system aimed at improving the efficiency of primary care in the UK by effectively handling the challenges of under-capacity clinics and unstructured data overload. Central to this system is the use of Qdrant, a vector search and similarity analysis platform, which aids in processing large volumes of unstructured clinical data while ensuring privacy. Anima employs Qdrant for clinical document coding, enabling the extraction of precise medical ontologies like SNOMED codes through large language models. Qdrant's deployment flexibility and cost predictability, alongside its vector-native capabilities, allow Anima to maintain compliance and experiment with multiple embedding strategies. The integration of Qdrant has resulted in scalable, privacy-first AI solutions, which facilitate faster document processing and informed patient care. As Anima continues to expand, it focuses on developing more autonomous clinical systems that remain compliant with regulatory constraints and adapt to evolving patient contexts, leveraging Qdrant's capabilities for continuous improvement in AI-driven healthcare delivery.