https://www.youtube.com/watch?v=hUwhmCgaocs

#Quasa #QUA #LlamaIndex

LlamaIndex is an open-source data framework plus LlamaCloud: parse, extract, classify, split, and index documents for RAG and agents. The Python/TS library is free. Cloud is credits. Official plans: Free 10,000 credits a month; Starter $50 with 40,000; Pro $500 with 400,000 and Slack; Enterprise custom. Credits cost $1.25 per 1,000. Fast parse is 1 credit a page; agentic plus is 45; some invoice presets hit 90. Cached re-parses can be free. LiteParse is local OSS with no tokens. It is not ChatGPT and not a finished knowledge base. Burn Free on your ugliest PDF. Buy Starter when 10K dies mid-week. Pro when concurrency and support matter.

𝐂𝗢𝗥𝗘 𝗦𝗧𝗥𝗘𝗡𝗚𝗧𝗛𝗦
• Strong tables, charts, handwriting parse
• OSS framework plus managed cloud
• Credit math you can forecast
• Extract with schemas, no training
• LiteParse for air-gapped work  

𝗜𝗗𝗘𝗔𝗟 𝗙𝗢𝗥
Teams stuffing PDFs into agents—finance, insurance, ops—who already know RAG is only as good as the parse.

𝗛𝗜𝗚𝗛𝗟𝗜𝗚𝗛𝗧𝗦
• 1B+ documents claimed processed
• Auto mode to cut page cost
• Startup credit program
• Hybrid / VPC on Enterprise
• Webhooks and caching  

𝗣𝗢𝗧𝗘𝗡𝗧𝗜𝗔𝗟 𝗖𝗢𝗡𝗦𝗜𝗗𝗘𝗥𝗔𝗧𝗜𝗢𝗡𝗦
• Agentic pages get expensive
• Free stops at 402 when empty
• PAYG caps on Starter/Pro
• Not a full LLM host
• Quality still depends on the scan  

𝗢𝗩𝗘𝗥𝗔𝗟𝗟 𝗩𝗘𝗥𝗗𝗜𝗖𝗧
4.5/5 stars. Keep the library. Pay Cloud only for pages that embarrass Tesseract. Watch credits like GPU time. Earn 1 QUA reward by reviewing on Quasa.io too!

𝗚𝗘𝗧 𝗦𝗧𝗔𝗥𝗧𝗘𝗗: https://quasa.io/projects/llamaindex