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Document Insights

You have 50 vendor contracts and one question: which ones auto-renew next quarter? Reading all 50 takes a day. Document Insights reads them for you and puts the answer in a table.

You tell Docana what to pull out of each document. It reads every document, extracts those fields, and lays the results out as a grid: one row per document, one column per field. What was 50 PDFs becomes a spreadsheet you can sort, filter, and ask questions about.

How It Works​

Create an application of type Document Insights, then build the table in three steps.

1. Define your columns​

A column is one thing you want from every document. Click Add Column and give it:

  • Name: what to call it, like "Renewal Date" or "Payment Terms"
  • Description: what to extract, written as an instruction, like "The date the contract automatically renews"

Add as many columns as you need. Each one becomes a column in the final table.

2. Add your documents​

Click Add Documents and pick the files or collections to analyze. Each document becomes a row.

3. Generate​

Click Generate Insights. Docana reads each document, pulls out every column you defined, and fills in the grid. A 50-contract, 4-field table is 200 values it extracts for you.

Document Insights table with one row per document and columns for the fields the user defined, each cell holding an extracted value
A Document Insights table: one row per document, one column per field you defined

Work With the Results​

Once the table is filled in, you can:

  • Sort and filter by any column to find what matters, like every contract renewing this quarter
  • Chat with it: open the playground and ask questions in plain English, like "which three contracts have the highest liability cap?"
  • Download it as a CSV, or save it to a collection

Turn Insights Into a Database​

The table you get is structured data, so it works like any other dataset. Save it to a collection and an agent can query it with SQL, the same way it queries an uploaded spreadsheet. Ask "what's the average contract value by vendor?" and the agent runs a real query against the extracted numbers.

So Document Insights closes the loop: unstructured documents go in, a queryable table comes out.

Example Uses​

  • Contracts: pull renewal dates, payment terms, and liability caps from every agreement, then sort by what's due soon
  • Resumes: extract years of experience, key skills, and certifications across a stack of applicants
  • Invoices: pull vendor, amount, and due date from each invoice into one table
  • Research: extract the method, sample size, and finding from a folder of papers

Best Practices​

  1. Write descriptions like instructions: "The total contract value in USD" extracts better than "value".
  2. One fact per column: separate "Renewal Date" and "Payment Terms" rather than one "Key Terms" column.
  3. Start small: define your columns on a handful of documents, check the results, then run the full set.
  4. Save it to query later: keep the output in a collection so an agent can answer number questions about it.

Next Steps​