Wissenswertes

Key Takeaways: Tran ran a nice experiment on PDF extraction, especially for tables, using different models/libraries In short: LlamaParse wins on speed and accuracy. It’s the fastest overall and produces the cleanest output, but it requires sending PDFs to LlamaCloud. Marker is the best local option. It’s faster than Docling and handles simple tables well, but it merges columns on dense layouts. Docling is the slowest of the three and prone to hallucinating values on dense ta

Key Takeaways: After n8n, Zapier & others now OpenAI launched its own workflow builder to build AI workflows for OpenAI Models: OpenAI Agent Builder Agent Builder enables users to create multi-Agent environments with tools , guardrails , vector storages , IF-ELSE-flow logics and more in a no-code UI Contrary, Google offers a Python library to create multi-Agent environments: Google SDK LangChain comments: "Not another workflow builder" Visual workflow builders are not “low”

Key Takeaways: LangChain Library can be used to integrate with Tableau APIs (vs. Tableau MCP) Critical: Data has to be clean and output...