Fileread Feature Highlight: Agentic Extraction

Feature Highlight: Agentic Extration - Turn Unstructured Documents into Actionable Data

In this installment of our Feature Highlight series, Fileread's Product Manager Wilfred Lai demonstrates how our Agentic Extraction tool transforms document analysis from tedious manual work into intelligent automation.

What is Agentic Extraction?

Agentic Extraction is Fileread's intelligent document processing tool that automatically extracts structured data from unstructured documents. Whether you're dealing with invoices, emails, court filings, or complaint forms, our tool identifies and organizes key information into easy-to-analyze tables.

See It in Action

In his video demo, Wilfred walks through a real-world example using documents from the McKinsey Purdue public case. The extraction tool quickly processed invoices to create a comprehensive table showing vendor names, addresses, invoice dates, customer information, and line items. What makes this powerful? Every extracted data point includes line-by-line citations back to the source document using our proprietary citation model.

Beyond Pre-Built Templates

While Fileread offers ready-made extraction workflows for common document types (invoices, emails, complaints, and court filings), the real magic happens when you need something custom. Wilfred demonstrates extracting data from 15000 email threads, starting with standard fields like sender, recipient, date, and CC.

But what if you need more? Simply describe what you want in plain language. When Wilfred asked the tool to analyze "the tone and language used in this email thread," the system intelligently suggested five relevant columns: overall tone, language formality, emotional content, use of jargon, and politeness markers. Each suggestion includes its own custom query to ensure accurate extraction.

Trust Through Transparency

Wondering how the system determined an email was "informal analytical"? Click any cell to view the exact text passages that informed that conclusion. This transparency ensures you can validate results and understand the AI's reasoning. Test extractions on a small sample before processing thousands of documents. This lets you refine your columns and queries, ensuring you're capturing exactly what you need before scaling up.

Ready to transform your document workflow? Watch our full demo to see Agentic Extraction in action and discover how natural language prompts can unlock insights hidden in your documents.