Business Idea: Develop a robust web data extraction platform leveraging LLMs to convert, process, and validate web content into structured, clean data for various applications, ensuring high accuracy and reliability.
Problem: Extracting structured data from web pages is challenging due to invalid JSON, broken links, and inconsistent content, making data automation and analysis difficult.
Solution: Create a library that converts HTML to LLM-friendly Markdown, processes data with LLMs using schema validation, and implements sanitization and URL validation to produce reliable, structured outputs directly from web content.
Target Audience: Data scientists, developers, startups, and enterprises needing automated web data extraction for analytics, NLP projects, or content aggregation.
Monetization: Offer the library as a paid API or SaaS platform with tiered subscription plans, providing enterprise-grade features, support, and customization options.
Unique Selling Proposition (USP): Combines robust HTML conversion, schema-driven processing with advanced LLMs, and comprehensive data sanitization and validation, ensuring high-quality structured data even with imperfect web content.
Launch Strategy: Start with a simple open-source version focused on HTML to Markdown conversion and basic JSON sanitization. Gather user feedback, then gradually add schema validation and URL validation features, promoting through developer communities and tech blogs.
Upvotes: 3
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