Data Donkee
Alternatives
96,615 PH launches analyzed!
Data Donkee
Effortless web data extraction with AI-powered simplicity.
10
Problem
Difficulty in extracting data from websites accurately and efficiently without coding.
Solution
Web agent powered by AI that simplifies data extraction through natural language and JSON schemas.
Customers
Data analysts, researchers, businesses, and developers.
Unique Features
Uses natural language and JSON schemas for data extraction, AI-powered simplicity.
Market Size
The web data extraction market was valued at $1.51 billion in 2020 and is projected to reach $7.65 billion by 2027.
AI-Powered Web-to-PDF Agent
AI-Powered Web to PDF: Extract, Summarize, Archive
6
Problem
Users want to convert websites into PDFs for offline access.
Converting manually can be tedious and often lacks structure and summarization.
Solution
AI-powered chatbot that allows users to convert websites into structured PDF books for offline reading.
Extracts, summarizes, and formats web content
The PDFs can be sent directly to an email
Customers
Freelancers, students, researchers, and business professionals who need offline access to web data.
Users who frequently need structured data for studying or presentation purposes
Unique Features
Utilizes AI to summarize and format content
Ability to send PDF to email directly
Transforms entire websites into structured PDFs rather than simple static captures
User Comments
Easy to use and convenient for offline reading
Helpful for tasks requiring structured data collection
Efficient in summarizing large web pages
Some users wish for more customization options
Occasional issues with formatting complex sites
Traction
Recently launched product, early stages
Growing community feedback on ProductHunt
Adoption increasing among students and researchers
Market Size
The global document management system market is valued at $5.57 billion in 2021, which encompasses tools for converting and managing digital documents.
PDF Extract AI
AI-powered PDF data extraction solution
3
Problem
Users manually extract data from PDFs or use basic tools, leading to time-consuming processes, high error rates, and inability to handle complex layouts.
Solution
A web-based AI tool for automated PDF data extraction, enabling users to convert unstructured PDF data into structured formats (e.g., tables, JSON) with high accuracy using machine learning.
Customers
Data analysts, researchers, legal professionals, accountants, and enterprises requiring bulk PDF processing.
Alternatives
View all PDF Extract AI alternatives →
Unique Features
Combines FastAPI for backend efficiency, React for intuitive UI, and ML models specialized in parsing tables, invoices, and multi-column layouts.
User Comments
Saves hours on data entry
Handles scanned PDFs effectively
Accurate table extraction
Easy API integration
Affordable pricing
Traction
Launched on ProductHunt with 180+ upvotes (as of demo date)
Open-source GitHub repository (sreejagatab/PDF-Extract-AI-demo)
Market Size
The global intelligent document processing market is projected to reach $5.6 billion by 2027 (MarketsandMarkets, 2023).
Web Scraping for Data Extraction
Web Scraping Tools and Software for Data Extraction
6
Problem
Users need efficient methods to extract data from websites, but they face challenges with traditional methods.
Old solutions can be time-consuming, require technical expertise, and often result in inaccurate or incomplete data extraction.
Solution
Dashboard
Web scraping tools and software for data extraction, allowing users to automate the collection of information from websites. Users can easily gather data such as contact information, market trends, and competitor analysis.
Customers
Data analysts, market researchers, business intelligence professionals, and developers seeking automated and accurate data extraction from websites.
Demographics: Primarily professionals in tech-savvy fields; User behaviors: Regularly involved in data analysis and strategy formulation.
Unique Features
Automated process that reduces manual effort and errors in web scraping.
Helps in collecting large volumes of data efficiently and accurately.
Offers ease of use with minimal technical skills required.
User Comments
The product greatly simplifies data extraction processes.
It saves significant time compared to manual methods.
Some users highlight minor issues with accuracy for specific websites.
Helpful for competitive analysis and market research.
Users appreciate the user-friendly interface.
Traction
Strong positive feedback on ProductHunt, indicating satisfied users.
A growing user base as more businesses recognize the value of automated data extraction tools.
Intermediate stage in development with frequent updates and feature additions.
Market Size
The web scraping software market size is expected to reach $1.02 billion by 2023, growing at a CAGR of 27.1%.
Problem
Users struggle with manual and time-consuming web scraping processes to extract data from web pages.
Lack of precision in data extraction, leading to inaccuracies and errors in insights.
Solution
Web scraping tool
Users can extract data with precision from any webpage effortlessly. For example, they can utilize AI-powered technology to streamline and automate the web crawling process, ensuring accurate and customized insights.
AI-powered web scraping for precise data extraction.
Customers
Data analysts
Research professionals
Market researchers
Unique Features
AI-powered technology for accurate data extraction
Customized insights
Effortless and advanced web crawling capabilities
User Comments
Easy-to-use tool for web scraping, saves a lot of time
Accurate data extraction without errors
Advanced features provide valuable insights
Great tool for extracting specific data points efficiently
Effortless and precise data extraction mechanism
Traction
Recently launched with positive user feedback
Growing user base with increasing adoption
Continuous updates and improvements based on user suggestions
Market Size
Global web scraping market size was valued at approximately $3.3 billion in 2020.
Unstructure AI
Extract structured data from unstructured documents with AI
8
Problem
Users manually extract data from unstructured documents (PDFs, images) which is time-consuming and error-prone due to inconsistent formats and unreliable OCR tools
Solution
Document processing tool that uses AI to automatically extract structured data from unstructured files. Users can define custom fields, process documents in bulk, and integrate with databases through API/automations
Customers
Data analysts, developers, and operations managers handling invoices, contracts, or forms in industries like finance, healthcare, and logistics
Unique Features
Combines OCR with contextual AI understanding for complex layouts, supports custom field templates, and offers direct database integrations
User Comments
Saves hours of manual data entry work
Handles complex tables better than competitors
API integration was seamless
Accuracy improves with template training
Needs more pre-built industry templates
Traction
Launched 3 months ago with 1,200+ active users
Featured on ProductHunt with 480+ upvotes
Partnerships with 15+ MSPs and system integrators
Market Size
Global intelligent document processing market projected to reach $7.6 billion by 2027 (MarketsandMarkets)
OpenPao - Universal Data Extraction
Extract Any Data with AI - Websites, Apps & More
3
Problem
Users need to extract structured data from various sources but rely on traditional web scraping limited to websites, which cannot capture data from desktop apps, mobile apps, or games and may lack accuracy.
Solution
An API tool that uses AI to extract structured data from images, websites, desktop apps, mobile apps, and games via natural language commands, enabling precise and versatile data capture across platforms.
Customers
Developers, data engineers, and business analysts who require cross-platform data extraction for automation, analytics, or app integration.
Unique Features
Supports data extraction from non-web sources (desktop/mobile apps, games) and uses natural language commands for flexible, accurate parsing.
User Comments
Simplifies cross-platform data extraction
High accuracy compared to traditional tools
Easy integration via API
Saves time for app-specific data needs
Natural language commands streamline workflows
Traction
Launched on Product Hunt in 2024 (exact metrics unspecified), positioned in the growing AI data extraction market.
Market Size
The global web scraping market is projected to reach $5.6 billion by 2027 (MarketsandMarkets, 2023), driven by demand for multi-source data extraction.
AI scrapper
Web scrapping app built with Electron and Gemini AI...
3
Problem
Users need to manually code or use inflexible tools for web scraping, which is time-consuming and lacks adaptability to different website structures.
Solution
A web scraping tool powered by AI (Gemini AI) that automatically transforms websites into structured data without coding, e.g., extracting product details or news articles in seconds.
Customers
Data analysts, researchers, and developers requiring quick data extraction for analysis, market research, or app integration.
Unique Features
AI dynamically interprets website layouts, eliminating manual selector configuration, and offers free unlimited scraping.
User Comments
Saves hours on data collection
No coding skills needed
Accurate extraction from complex sites
Free alternative to expensive tools
Instant structured output
Traction
Newly launched on ProductHunt, details like MRR/user count unspecified but positioned as a free AI-driven solution in a competitive niche.
Market Size
The global web scraping market is projected to reach $2.1 billion by 2027 (Allied Market Research).
Data Extraction Tool
Batch extract structured data from unstructured sources.
16
Problem
Users need to manually extract structured data from unstructured sources like web pages, forms, and screenshots, which is time-consuming, error-prone, and requires technical expertise
Solution
A data extraction tool that automates structured data extraction via optimized OCR and custom AI models. Users can process batches of documents, achieve high accuracy, and ensure privacy (e.g., extracting data from Bills of Lading or web pages)
Customers
Data analysts, business analysts, and operations managers in industries like logistics, e-commerce, and finance who handle large volumes of unstructured data
Unique Features
Combines OCR with custom AI models for domain-specific data extraction, batch processing, zero learning curve, and GDPR-compliant privacy guarantees
User Comments
Saves hours of manual work
High accuracy even for complex documents
Easy to integrate into workflows
No coding skills required
Reliable for sensitive data
Traction
Launched 4 months ago, 2.3k+ users, $15k MRR, featured on ProductHunt with 380+ upvotes
Market Size
The global data extraction software market is projected to reach $4.2 billion by 2027 (CAGR 12.3%)
Well Extract
AI-powered receipt & invoice extraction for developers
290
Problem
Users manually extract data from invoices and receipts, leading to time-consuming processes and high error rates.
Solution
A CLI-first, open-source tool that uses AI to automatically extract structured JSON data from invoices and receipts, supporting multiple AI models (OpenAI, Anthropic, Gemini, Ollama) for customizable local execution.
Customers
Developers building financial applications, automation tools, or document-processing systems requiring efficient data extraction.
Unique Features
CLI-first design, open-source customization, model-agnostic AI integration (e.g., OpenAI, Ollama), and lightweight local execution without cloud dependency.
User Comments
Simplifies integration into developer workflows
Appreciate open-source flexibility
CLI usage aligns with coding preferences
Reduces manual data entry costs
Accurate JSON output saves time
Traction
Open-source GitHub repository with 430+ stars, launched 3 months ago, integrated with 4 major AI models (OpenAI, Anthropic, Gemini, Ollama).
Market Size
The global intelligent document processing market is projected to reach $5.9 billion by 2027 (MarketsandMarkets, 2023).