Case StudyAutonomous
Autonomous
Data Science
10,000+
Docs Processed
-60%
Manual Work
95%
Accuracy
Semantic
Search
Untapped Labs
Untapped Labs –
AI Automations
A biotech research firm drowning in unstructured clinical trial data.
The Challenge
Researchers spent 60% of their time manually categorizing research papers.
Our Solution
Deployed a custom RAG (Retrieval-Augmented Generation) pipeline to automatically summarize and categorize PDFs.
Base Architecture
Integration Layer
Performance Node
Performance Data
Growth Trajectory
10,000+
Docs Processed
-60%
Manual Work
95%
Accuracy
Semantic
Search
Project Highlights
RAG Pipeline: Vector database integration for semantic search over vast PDF archives.
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