According to Andrew Ng, Agentic Document Extraction has reduced its median processing time from 135 seconds to just 8 seconds, enabling rapid extraction of not only text but also diagrams, charts, and form fields from PDFs for LLM-ready output (source: Andrew Ng on Twitter, May 27, 2025). This significant performance upgrade can accelerate automated data ingestion for crypto trading algorithms and decentralized finance analytics, offering traders a competitive edge in processing and acting on real-time document-based data.

According to Andrew Ng, the newly announced Agentic Document Extraction leverages advanced techniques to interpret PDFs beyond mere text extraction, focusing on visual elements like layout and charts, which is crucial for traders analyzing complex financial documents. This approach could significantly enhance the precision of data extraction from financial reports and forecasts, providing traders with more accurate and actionable insights.