Vellparser

Vellparser

Turn your documents into structured data with AI

ievolve
@ievolve
Published on Jul 24, 2026
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Details

Pricing
Freemium from $14
Platforms
Web
Alternative To
ParseExtract

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How AI and people discover Vellparser on PeerPush

AI-readyAI-readyWhether this product carries the structured data - use cases, audiences, platforms - that lets AI match it to the right questions.
Structured

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Described for AI with use cases, audiences, platforms and pricing so assistants can match it to the right questions.
Discoverable nowDiscoverable nowWhether this product is queryable through the PeerPush API and MCP right now.
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Via the PeerPush API and MCP

Queryable through the PeerPush API, MCP and semantic search from day one.

About Vellparser

Vellparser is an AI-powered data extraction tool that transforms PDFs, images, invoices, receipts, forms, reports, and other documents into clean, structured data. It helps individuals and teams replace repetitive copy-and-paste work with a faster and more consistent document-processing workflow. Getting started is simple. Define the information you want to capture, such as names, dates, invoice numbers, totals, addresses, IDs, table rows, line items, or custom fields. Upload your document, and Vellparser analyzes its text, labels, tables, context, and visual structure to extract the requested information. You can then review the results before exporting or using them in spreadsheets, databases, internal tools, and automation workflows. Unlike basic OCR software that only converts visible text into machine-readable content, Vellparser focuses on understanding what the information means and organizing it into the structure you need. It can work with scanned PDFs and image-based documents, while also handling documents whose layouts vary from one file to another. For recurring workflows, reusable extraction rules make it easy to process similar invoices, forms, receipts, and reports without rebuilding the setup for every upload. This helps teams reduce manual data entry, catch errors before information reaches downstream systems, and prevent document-processing backlogs from growing. Vellparser is also designed with sensitive document data in mind. Files and extraction results remain private, data is encrypted in transit, access requires authentication, and uploaded documents, extraction instructions, and results are not used to train AI models.

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