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Data for AI

Power your AI with high-quality data

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About Data for AI

What is “Data for AI” (Forage AI) Data for AI is Forage AI’s solution for delivering AI-ready training data—fully extracted, cleaned, and structured—so teams can train or fine-tune machine-learning models without handling complex data collection workflows. Instead of manually scraping, parsing, and formatting data from multiple sources, Forage AI provides high-quality datasets directly in ML-friendly formats. What Types of Data Are Supported? Forage AI processes data from: - Webpages and dynamic websites - Documents such as PDFs, company reports, financial filings, research papers, and presentations - Public records and government information - Market data and structured tables - Images, charts, and visual information - Social media and community-generated content - Other unstructured and semi-structured sources Scale of coverage: - 500M+ websites crawled - 10M+ documents parsed - 50,000+ datasets available - Coverage across 20+ industries Two Modes: Custom Extraction vs Ready-Made Datasets 1. Custom Data Extraction For specialized needs, Forage AI provides: - Tailored extraction and parsing workflows - Dataset annotation - Flexible output formats - High-volume processing (millions of records) - A dedicated extraction team for end-to-end support 2. Ready-Made Datasets Pre-processed, validated, and consistently structured datasets ready for immediate integration into AI and ML workflows. Why Leading Brands Trust This Data Extraction Process - Precision extraction: AI-powered methods deliver highly accurate, structured data. - Broad data coverage: Supports multiple formats and source types for richer model training. - Strong ML expertise: Built with deep knowledge of machine learning and data processing. - Ethical and compliant: Follows global data standards like GDPR and CCPA to ensure responsible usage. Who Benefits from Data for AI? Ideal for teams that need: - Clean, structured data for training or fine-tuning ML models (LLMs, NLP, document AI, analytics models) - Automated workflows that turn unstructured web and document data into usable ML inputs - Industry-specific data across finance, healthcare, real estate, social media, market research, public records, and more

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