Clinicians face persistent challenges in retrieving critical information from complex medical documents, impacting care quality and efficiency. In this technical case study, learn how Eolas Medical partnered with LandingAI to transform clinical knowledge access using Agentic Document Extraction (ADE).
Key Topics
Challenges in Clinical Knowledge Access:
- Difficulties in locating vital clinical information embedded in text, diagrams, and tables
- Risks of delays, errors, and reduced clinician trust
Solution Overview
- Integration of LandingAIโs ADE API with Eolas Medicalโs platform
- Intelligent indexing and layout-aware parsing of clinical documents
- Use of Retrieval-Augmented Generation (RAG) and vector-based retrieval for precise answers
- Pinpoint sourcing with direct references to original diagrams, tables, and guideline sections
- Zero configuration deployment across 400+ medical centers
Results & Impact
- 90% reduction in time spent searching for clinical information
- 100% source attribution for all AI-generated answers
- 87% of clinicians said a healthcare-specific engine like Ask Eolas is better than general AI tools like ChatGPT
Watch for a deep dive into the solution, deployment, and measurable benefits of AI-powered document intelligence in healthcare.
Get started with Agentic Document Extraction: https://va.landing.ai/demo/doc-extraction
