PDF Vector

Excel to structured data for no-code users

Turn your Excel spreadsheets into structured data. Seamlessly integrate with many no-code automation platforms.

Schema-Driven Extraction – Define your data structure with JSON Schema and get perfectly formatted results every time

No-Code Automation Ready – Native integration with n8n, Make, and Zapier - build powerful data workflows without writing code

Battle-Tested Reliability – Proven in production by Research Kick and ChatAcademia, processing hundreds of Excel files daily with consistent results

What people are saying

See how PDF Vector is helping teams improve their document processing workflows

“Can't recommend PDF Vector enough! It boosts your AI workflow accuracy to 100% while dropping your costs! Especially if you're a T4 Org in the $150/m spend range!”

— Abdo El-Mobayad

“Gotta give a shoutout to PDF Vector team for helping me set up PDF Vector for a project. They even delivered on a feature request before I purchased. Incredible customer service. 👏”

— Trent

“Been implementing RAG and changing a lot of things under the hood for @rabbitholesai, came across PDF Vector and it was a huge time saver. I got a document parsing solution for the rag pipeline within minutes! one less thing to worry about”

— Praneeth Pike

Built for every use case

Extract structured data from Excel spreadsheets using AI and JSON schemas. Perfect for financial reports, inventory lists, employee data, and more.

Contract parsing

Invoice extraction

Financial reports

Form processing

Business intelligence

ChatGPT integration

Document chatbots

RAG systems

Semantic search

API integrations

Data mining

Table extraction

Chart analysis

Content indexing

Digital archives

Ready-to-use templates

Get started quickly with our pre-built templates for common PDF Vector workflows in n8n, Make, and Zapier

n8n

Extract Invoice Data with PDF Vector and Google Drive

Automatically extract structured data from PDF invoices or invoice images stored in Google Drive, validate information, and integrate with accounting systems.

Open on n8n

n8n

Parse and Score Resumes with PDF Vector AI

Automate resume screening by extracting candidate information, skills, and experience, then score against job requirements.

Open on n8n

n8n

Analyze Legal Contracts with PDF Vector Risk Assessment

Review legal contracts automatically by extracting key terms, identifying potential risks, and flagging unusual clauses.

Open on n8n

n8n

Build Document Q&A API with PDF Vector and Webhooks

Create an intelligent document Q&A system that can answer questions about uploaded documents using AI.

Open on n8n

n8n

Extract and Analyze Research Papers with PDF Vector Academic Tools

Automatically analyze research papers by parsing PDFs, extracting key information using AI, and storing results for future reference.

Open on n8n

n8n

Automated Receipt Processing with Tax Categorization

Automatically process expense receipts by extracting purchase details and categorizing expenses for tax reporting.

Open on n8n

n8n

HIPAA-Compliant Medical Document Processor

Extract structured data from medical documents while maintaining HIPAA compliance and patient privacy protection.

Open on n8n

n8n

Automated Literature Review with Citation Management

Automate literature review creation by analyzing multiple research papers, organizing citations, and generating comprehensive reviews.

Open on n8n

n8n

Comprehensive Legal Research Assistant

Extract and validate legal citations from court documents, ensuring accuracy and proper legal formatting.

Open on n8n

n8n

Enterprise Document Processing Pipeline

Process large volumes of documents and create comprehensive analytics dashboards with insights and visualizations.

Open on n8n

Example Output

Real examples of structured data extracted from Excel spreadsheets

Original Document

Income statement

Output

AI-generated answer to your question

Question

Extract all income statement details

Schema

{
  "type": "object",
  "properties": {
    "company_name": {
      "type": "string"
    },
    "period_ending": {
      "type": "string"
    },
    "revenue": {
      "type": "number"
    },
    "expenses": {
      "type": "number"
    },
    "net_income": {
      "type": "number"
    }
  }
}

Answer

{
  "company_name": "Quinn Campbell",
  "period_ending": "FYXX Q2",
  "revenue": 500654,
  "expenses": 474171,
  "net_income": 63841
}

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Excel to structured data for no-code users

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What people are saying

Built for every use case

Ready-to-use templates

Example Output

One subscription, all APIs

Ready to Extract Data at Scale?

Everything you need for document processing

Frequently asked questions