ChatPDF API

Development Tools · AI & ML

The ChatPDF API provides a simple interface for uploading PDF documents and querying their content using natural language questions, powered by AI. It allows developers to build document intelligence features into their applications — giving users the ability to ask questions about a PDF and receive accurate, cited answers without reading the entire document.

freemium

API Key

Per plan limits on PDF uploads and questions

✗ Not Available

Best For

Nigerian developers building document intelligence applications that need to upload PDFs and ask natural language questions about their content using AI.

Pricing

ChatPDF API enables uploading PDFs and querying their contents via natural language questions backed by AI (similar to ChatGPT for documents). Returns cited answers from the document. Great for legal, compliance, and research applications.

Key Highlights

  • Upload PDF via URL or file
  • Natural language Q&A on PDFs
  • AI-powered answers with citations
  • Multi-turn conversations
  • Multiple languages
  • REST API
  • Freemium pricing
  • No custom ML model needed

Required Access Documents

  • API KeyRequired
    Register at chatpdf.com to get an API key. Pass as Authorization header: Bearer {key}.

Use Cases

  • Nigerian Legal Document Q&A System:Nigerian law firms and legal tech platforms can use ChatPDF API to allow lawyers and clients to ask natural language questions about contracts, court judgments, regulatory documents, and legal opinions — getting instant cited answers without reading entire documents.
  • Nigerian Financial Report Analysis Tool:Nigerian investment analysts and finance teams can upload annual reports, prospectuses, and regulatory filings to ChatPDF API and query specific financial metrics, risk factors, or management statements — dramatically accelerating financial document review.
  • Nigerian Student Research Assistant:Nigerian university students and researchers can build tools using ChatPDF API to query academic papers, textbooks, and research reports in natural language — extracting key information and understanding complex documents more efficiently than manual reading.

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