Extend: Turning Messy Documents into Data
Analysis
Extend offers a toolkit for AI teams to process messy documents (PDFs, images, Excel files) and build products. The founders highlight the challenges of handling complex documents and the limitations of existing solutions. They provide a demo and mention use cases in medical agents, bank account onboarding, and mortgage automation. The core problem they address is the difficulty in reliably parsing and extracting data from a wide variety of document formats and structures, a common bottleneck for AI projects.
Key Takeaways
- •Addresses a common pain point for AI teams: reliable document processing.
- •Focuses on handling complex and messy document formats.
- •Provides APIs for parsing, classifying, splitting, and extracting data.
- •Has real-world applications in various industries (medical, finance).
Reference
“The long tail of edge cases is endless — massive tables split across pages, 100pg+ files, messy handwriting, scribbled signatures, checkboxes represented in 10 different formats, multiple file types… the list just keeps going.”