Data Extraction Software for Documents

Data extraction software reads a document and returns the specific values you care about as structured data. Instead of someone copying an invoice total or a policy number into a spreadsheet, the software finds the value, labels it and outputs it in a consistent format.

Template-based data extraction tools ask you to map where each field sits on the page, and each new layout needs its own template. AI data extraction identifies fields by what they mean, so you do not need to build a template for every layout of the same document type.

super.AI is data extraction software built for operations teams, not only developers. You describe the fields in plain language and super.AI builds the flow. When the documents are complex, super.AI's experts help you build it.

#Data extraction from documents, not websites or databases

"Data extraction tools" can mean several things. Web scraping tools collect data from websites, and ETL tools move data between databases. This page is about data extraction from documents: invoices, forms, shipping paperwork and other files your team receives. That is the work super.AI is built for.

1. Upload a real document. Use a PDF, an image or an email attachment from your own queue.
2. Describe the fields you need. For example: "Extract the policy number, claimant name and date of loss from each claim form."
3. Check the flow. super.AI builds the extraction flow and shows each step, so you can see what it reads and what it returns.
4. Review exceptions. Low-confidence results go to a human review view. Your corrections carry into the next run.
5. Export. Send the structured data to CSV, JSON or Google Sheets.

Free to start, no credit card and no sales call required. Start for free, or book a demo if you want super.AI's experts to help you build it.

Scans, photos and unusual layouts make some values hard to read for any extraction tool. In practice, accuracy depends on what happens to uncertain values. When super.AI has low confidence in a result, it goes to a review view instead of straight into your data, and a person confirms or corrects it.

Values super.AI is confident about go straight to your export, and the rest wait for a person. Those corrections carry into the next run, so your flow keeps learning from your team's fixes.

• Setup: templates and rules, or a plain-language description of the fields?
• Inputs: PDFs, images and email attachments, or only clean digital files?
• Review: is there a built-in place for people to check low-confidence values?
• Learning: do corrections carry into the next run, or do you fix the same error every week?
• Output: can you export to formats your team already uses, such as CSV, JSON or Google Sheets?
• Security: are commitments such as SOC 2 Type II available when you need them? super.AI offers SOC 2 Type II coverage and contractual commitments to enterprise customers.

• Invoices: invoice numbers, vendor details, dates and payment terms. See invoice data extraction.
• Bills of lading: shipper, consignee and carrier details. See bill of lading automation.
• Purchase orders: PO numbers, items and quantities. See purchase order processing.
• Insurance claim forms: policy numbers, claimant details and dates of loss. See claim form data extraction.

When extraction is one step in a bigger process, see document workflow automation. For background on the technology, see intelligent document processing.