PDF Vector
PDF Vector is an AI-powered document processing platform that enables developers and no-coders to parse documents, extract structured data, ask AI questions about documents, and search academic papers through a unified API.
https://www.pdfvector.com/?ref=producthunt
Product Information
Updated:Oct 17, 2025
What is PDF Vector
PDF Vector is a comprehensive document processing solution that helps teams and developers handle various types of documents including PDFs, Word files, Excel spreadsheets, and images. It combines artificial intelligence with powerful parsing capabilities to transform documents into clean, structured text while also providing academic paper search functionality across major research databases. The platform is designed to be developer-friendly with simple API integration options, while also catering to no-code users through easy-to-use interfaces.
Key Features of PDF Vector
PDF Vector is an AI-powered document processing API service that enables developers and no-coders to transform various document types (PDFs, Word files, Excel spreadsheets, and images) into clean text, extract structured data, and perform AI-based queries. It also provides access to over 5M academic papers and offers features for parsing, asking questions, and searching academic content through a unified API interface.
Document Parsing & Conversion: Converts various document formats into clean, structured markdown text while maintaining document integrity and formatting
AI-Powered Document Q&A: Allows users to ask questions about documents and receive answers in markdown format using advanced AI processing
Academic Paper Access: Provides search and retrieval capabilities across multiple academic databases including PubMed, Semantic Scholar, ArXiv, and more
Structured Data Extraction: Extracts specific data points and information from documents using customizable fields and parameters
Use Cases of PDF Vector
Research & Academic Analysis: Helps researchers and students efficiently process academic papers, conduct literature reviews, and track citations
Business Document Processing: Automates the extraction and processing of contracts, invoices, and financial reports for business intelligence
AI Integration & RAG Systems: Enables seamless integration with ChatGPT and other AI tools for building document chatbots and RAG (Retrieval-Augmented Generation) systems
Pros
Excellent customer service with responsive support
Easy integration with simple API and TypeScript SDK
Comprehensive feature set covering multiple document types
Flexible pricing plans starting with a free tier
Cons
Credit-based pricing may become expensive for high-volume usage
Limited customization options for specific industry needs
How to Use PDF Vector
Sign up and get API key: Visit pdfvector.com and sign up for a free account to get your API key (format: pdfvector_xxxxxxx)
Install the SDK: Install the TypeScript SDK by running 'npm i pdfvector' in your project
Initialize the client: Import and initialize the PDFVector client with your API key: const client = new PDFVector({ apiKey: 'pdfvector_xxxxxxx' })
Parse documents: Use the parse() method to process documents either from URL or file: await client.parse({ url: 'https://example.com/document.pdf', useLLM: 'auto' }) or from local file using readFile
Extract data: Use the extract functionality to get structured data from documents with custom fields based on your needs
Ask questions: Use the ask() method to query documents and get AI-powered answers in markdown format
Search academic papers: Use the academic search functionality to search across multiple academic databases like PubMed, ArXiv, Google Scholar etc.
MCP Integration (Optional): For AI assistant integration, add PDF Vector to your MCP configuration using: claude mcp add --transport http --scope user pdfvector https://www.pdfvector.com/mcp --header 'Authorization: Bearer [API_KEY]'
PDF Vector FAQs
PDF Vector is an AI-powered document processing API that helps convert documents into clean text, extract structured data, ask AI questions about documents, and search academic papers through a unified API.
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