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RAG engine that just works for complex real-world documents. It can extract knowledge from unlimited tokens across ANY data format - Word docs, Excel sheets, PDFs, and even scanned copies. And it's 100% Opensource.

Shubham Saboo

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45,212 görüntüleme • 11 ay önce •via X (Twitter)

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Building RAG is easy. Parsing real, unstructured data is the hard part. Most tools fail when documents get complicated. RAGFlow by InfiniFlow makes the entire process visual and flawless 🔥 It is an (open-source!) engine built specifically to find the exact needle in a data haystack, even across literally unlimited tokens. The platform comes packed with: → "Quality in, quality out" parsing for highly complex formats → Multiple recall paired with fused re-ranking → A built-in Python and JavaScript code executor for agents → An orchestrable ingestion pipeline Here's why it stands out: 1️⃣ Structural Understanding Instead of just scraping text, it handles tables across pages, scanned copies, slides, and Excel sheets natively using deep document understanding. 2️⃣ Grounded Citations Every answer is verifiable. The UI highlights the exact chunks used, allowing you to trace any response directly back to the source material. 3️⃣ Enterprise Synchronization Keep your context constantly updated with native data sync from Google Drive, Notion, Discord, and Confluence. Stop letting bad document parsing ruin your RAG systems. Best part? It's 100% Free and open-source. Link to the repo in 🧵↓

Building RAG is easy. Parsing real, unstructured data is the hard part. Most tools fail when documents get complicated. RAGFlow by InfiniFlow makes the entire process visual and flawless 🔥 It is an (open-source!) engine built specifically to find the exact needle in a data haystack, even across literally unlimited tokens. The platform comes packed with: → "Quality in, quality out" parsing for highly complex formats → Multiple recall paired with fused re-ranking → A built-in Python and JavaScript code executor for agents → An orchestrable ingestion pipeline Here's why it stands out: 1️⃣ Structural Understanding Instead of just scraping text, it handles tables across pages, scanned copies, slides, and Excel sheets natively using deep document understanding. 2️⃣ Grounded Citations Every answer is verifiable. The UI highlights the exact chunks used, allowing you to trace any response directly back to the source material. 3️⃣ Enterprise Synchronization Keep your context constantly updated with native data sync from Google Drive, Notion, Discord, and Confluence. Stop letting bad document parsing ruin your RAG systems. Best part? It's 100% Free and open-source. Link to the repo in 🧵↓

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Grok 4.3 just started dropping full files. It spits out Word docs, PDFs, slides, and spreadsheets. Just like that. No back and forth. No hacks. Just done. You ask once… it builds the whole thing. Nice. @xAI @Grok

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Introducing /extract v2 🚀 Now you can extract from multiple pages, handle pagination, and even extract from the entire web without a URL - powered by FIRE-1. Our state of the art endpoint that allows you get data with a prompt just got a lot better on Day 3 of Launch Week.

Introducing /extract v2 🚀 Now you can extract from multiple pages, handle pagination, and even extract from the entire web without a URL - powered by FIRE-1. Our state of the art endpoint that allows you get data with a prompt just got a lot better on Day 3 of Launch Week.

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INSANE...this is an Open Source Video model available for free on Hugging Face. LongCat just dropped an amazing video avatar model that can do crazy things. And it's 100% Opensource.

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You can now directly add content from Google Docs to chats and projects. Just paste a link or choose from recent documents to get started.

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Anthropic

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Not all Excel can do this. Try and see if it works.

Not all Excel can do this. Try and see if it works.

Eyo Eyo, PhD

11,529 görüntüleme • 4 ay önce

6. You can easily add content from Google Docs to your chats and projects. Just paste a link or pick from your recent documents to begin.

6. You can easily add content from Google Docs to your chats and projects. Just paste a link or pick from your recent documents to begin.

Rimsha Bhardwaj

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$4.4 trillion in PE assets under management Monitored by analysts who spend 500+ hours a year copying numbers from PDFs into Excel. Not analyzing. Copying and pasting. A fund has 10 portcos. One on NetSuite, one on QuickBooks, three on Excel, one CFO sending a paragraph in an email every quarter. Company A calls it "Revenue." Company B calls it "Net Sales." Company C doesn't even use the same EBITDA calculation. Before AI can do anything useful, you need four layers: 1. Ingestion: get the data out of PDFs, spreadsheets, emails, whatever format it shows up in 2. Normalization: make sure the same metric means the same thing across every company 3. Storage: structured database that can actually be queried, not a folder of files 4. Query layer: natural language interface so a non-technical partner can ask "which portco is trending down on margins?" and get a real answer Most companies jump straight to layer 4 and wonder why nothing works. The unlock is building layers 1-3 first. Once those exist, the AI part is MUCH easier. The firms that get their data infrastructure right first will be untouchable.

$4.4 trillion in PE assets under management Monitored by analysts who spend 500+ hours a year copying numbers from PDFs into Excel. Not analyzing. Copying and pasting. A fund has 10 portcos. One on NetSuite, one on QuickBooks, three on Excel, one CFO sending a paragraph in an email every quarter. Company A calls it "Revenue." Company B calls it "Net Sales." Company C doesn't even use the same EBITDA calculation. Before AI can do anything useful, you need four layers: 1. Ingestion: get the data out of PDFs, spreadsheets, emails, whatever format it shows up in 2. Normalization: make sure the same metric means the same thing across every company 3. Storage: structured database that can actually be queried, not a folder of files 4. Query layer: natural language interface so a non-technical partner can ask "which portco is trending down on margins?" and get a real answer Most companies jump straight to layer 4 and wonder why nothing works. The unlock is building layers 1-3 first. Once those exist, the AI part is MUCH easier. The firms that get their data infrastructure right first will be untouchable.

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