RAG-Based Approaches for Life Science Applications

Join Sinequa and SciBite for our Live Webinar!

The heterogeneity, complexity and fast moving evolution of terminology in the life sciences presents particular challenges. As companies scramble to implement AI, vector based search is an obvious entry point, allowing users to support semantic search without the need for experts to curate ontologies. This allows users to get up and running faster and to evaluate RAG based approaches for LLM implementation.

What is becoming evident, is that using vector-based search for RAG architecture has limitations, particularly in the life sciences and where accuracy, transparency and explainability are important.

In the life sciences particularly, vector search can struggle to distinguish concepts that are very close in vector space such as synonyms and this is where an ontology, curated by subject matter experts really improves search and analytics. The aim of this webinar will be to outline this hybrid approach of combining vector search (Neural Search) with ontology based semantic search and how this provides the best of both approaches.