🚀 Now in Beta

Stop Letting Document Data Slow You Down

Get key details out of PDFs, scans, and forms, and into your Postgres tables. Accurate. Automatic. No manual work.

Small Delays Add Up to Big Problems

Every time someone has to search for details, retype information, or fix manual errors, your team slows down. Data buried in documents means missed deadlines, mounting frustration, and work that grinds to a halt. Errors sneak in, customers wait longer, and no one trusts the numbers.

Data gets scattered across invoices, contracts, and forms: Critical information is locked away in different formats across different systems.
Manual entry leads to mistakes and wasted time: Every retyped number is a chance for error. Every manual process is hours lost.
Teams are stuck waiting for the information they need: Work grinds to a halt while someone searches for details buried in documents.
Decisions get made on incomplete or outdated data: When data is hard to access, people make choices without the full picture.

Document-to-Database in Three Easy Steps

Skip the bottlenecks. Go from unstructured documents to clean database tables with a simple, automated pipeline.

New documents are detected automatically: As soon as files arrive, the pipeline kicks into action. No manual triggers needed.
Key fields are extracted and mapped to your database schema: Your predefined fields are pulled from even the messiest documents with precision.
Data is loaded into Postgres, structured and ready for use: Clean, validated data flows directly into your tables. Query it, report on it, automate with it.

How Vectorize Works

Data Extraction Built for Real Workflows

Vectorize connects your storage, detects new documents, and uses Iris to extract the fields you define, even from complex layouts. All processing, validation, and mapping is handled for you. Your data flows straight into Postgres, ready for queries and automation.

Connect your source: Google Drive, S3, or wherever your documents live
Define the schema: for the information you care about
Iris processes and extracts: the data you need, reliably

Direct to Postgres

-- Your extracted data, ready to query
SELECT 
  invoice_number,
  vendor_name,
  total_amount,
  due_date
FROM extracted_invoices
WHERE due_date < CURRENT_DATE
  AND payment_status = 'pending'
ORDER BY total_amount DESC;

-- Results available immediately
invoice_number | vendor_name    | total_amount | due_date
INV-2024-001  | Acme Corp      | $12,450.00   | 2024-01-15
INV-2024-047  | Tech Solutions | $8,200.00    | 2024-01-18

Stop Letting Document Data Slow You Down

Small Delays Add Up to Big Problems

Document-to-Database in Three Easy Steps

How Vectorize Works

Direct to Postgres

Ready to automate your document workflows?