Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.
Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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...Multiple narratives can be listed in the text file, where narratives are separated using a # symbol.
The text upload process entitles the initial (POS) tagging of uploaded text using Stanford (POS) tagger.
The user can later modify and extend the initial tagging.
The resultant annotations are stored in the supporting database. These results can be exported to excel or text files for further processing.