KI-gestützte Plattform zum Scraping und zur Generierung von Blog-Inhalten

MicrocosmWorks implemented a multi-stage originality pipeline that first extracts key topics and factual claims from scraped content, then generates entirely new prose using GPT-4 with explicit instructions to rephrase and restructure. Each generated article passes through a plagiarism detection check against the source corpus, with a maximum 15% similarity threshold before regeneration is triggered.

MicrocosmWorks built a content quality classifier that scores scraped articles on readability, topical relevance, factual density, and engagement metrics before they enter the generation pipeline. Articles scoring below the quality threshold are discarded, and the system prioritizes authoritative sources by tracking domain authority scores and citation patterns across the scraped corpus.

Yes, MicrocosmWorks integrated keyword research data from SEMrush API feeds into the generation pipeline, so each article is produced with a target primary keyword, related secondary keywords, and semantically relevant entities. The generator outputs content with proper H2/H3 hierarchy, meta descriptions, and internal linking suggestions optimized for search intent.

MicrocosmWorks designed the pipeline for batch processing with configurable daily output quotas, topic scheduling, and editorial workflow integration. The system generates articles in parallel across multiple LLM API instances, with a queue manager that distributes topics evenly across content categories and maintains a publication calendar with WordPress or CMS auto-publishing support.

MicrocosmWorks delivers AI content automation platforms at rates of $20-$45/hr, with a full scraping and generation system including the quality classifier, SEO optimization, and CMS integration typically requiring 400-600 development hours. Ongoing LLM API costs for content generation scale with volume, typically running $0.05-$0.20 per generated article depending on length and model selection.