LlamaSheets is our new way to handle complex, messy spreadsheets that come as many sheets disguised as one, multiple regions that provide different sets of information, and much more. Check out this example of a (generated, fake) company budget sheet. It actually has 4

"ask" and you shall receive! SemTools now ships with a dedicated "ask" CLI command - performs agentic search over documents - combine with `parse` to create QA workflows over unstructured data - cache your indexes with `workspaces` Learn more:

Split documents into distinct sections automatically with our new LlamaSplit API 📄✂️ We're excited to introduce LlamaSplit (now in beta), which uses AI to automatically separate bundled documents into clear, targeted sections based on categories you define - no more manual

That outdoor brick oven isn't connected to anything. No kitchen. No house. Just vibes and one enormous orange vegetable. Peak architectural planning. Out now on Steam 👇

Scalably Parsing 1M+ PDFs with AI Agents 📈📑 Here’s a simple tutorial we wrote up showing you how to parse a directory of an arbitrary number of PDFs through our service in a reliable, efficient manner. LlamaParse is designed to handle very large workloads; with some simple

Need to parse multiple PDFs efficiently? Learn how to use LlamaParse with async batch processing. 📁 Process entire folders of PDFs simultaneously instead of one-by-one ⚡ Use asyncio and semaphores to control how many files parse concurrently 🎯 Prevent API rate limit errors

“Intelligent Document Processing” 📑🧪 as an industry is gone . With our latest release this week, *anyone* can build and deploy a specialized document agent in seconds ⚡️🤖, and customize the steps via code. Let’s take a tour through our invoice processing and contract matching

Document understanding is a huge use case for VLMs, but historically there's been no single "good" benchmark to measure progress here (unlike SWE-bench for coding). This past week I did a deep dive into OlmOCR-Bench, a recent document OCR benchmark that is a huge step in the

OCR benchmarks matter, so in this blog @jerryjliu0 analyzes OlmOCR-Bench, one of the most influential document OCR benchmarks. TLDR: it’s an important step in the right direction, but doesn’t quite cover real-world document parsing needs. 📊 OlmOCR-Bench covers 1400+ PDFs with

Deploy production-ready agent workflows with just one click from LlamaCloud. Here's us deploying the SEC filling extract and review agent! Our new Click-to-Deploy feature lets you build and deploy complete document processing pipelines without touching the command line: 🚀

Calling all community members: Join us this Thursday for an office hours in our Discord server, all about LlamaAgents and LlamaSheets. This is a chance to ask anything on your mind about two of our latest releases, and learn about what's coming up next. Drop in anytime from 11AM

Claude Code over Excel++ 🤖📊 Claude already 'works' over Excel, but in a naive manner - it writes raw python/openpyxl to analyze an Excel sheet cell-by-cell and generally lacks a semantic understanding of the content. Basically the coding abstractions used are too low-level to

Build scripts that automate spreadsheet analysis using coding agents and LlamaSheets to extract clean data from messy Excel files. 🤖 Set up coding agents like @claudeai and @cursor_ai to work with LlamaSheets-extracted parquet files and rich cell metadata 📊 Use formatting cues

Automate ETL over Financial Data 📊 Most real-world financials are not “database-shaped”, and requires a ton of human effort to manipulate/copy an Excel sheet into structured formats for analysis. We recently launched LlamaSheets - a specialized AI agent that automatically

POV: You're building an agent and it keeps giving weird answers because your PDF parsing is broken 🫠 This is a great walkthrough by @mesudarshan showing exactly how to use LlamaParse to fix this—from basic setup through advanced configs. The video walks through: · Why most PDF

Stop losing 80% of your data when extracting from long documents with repeating entities like catalogs, tables, and lists. Our new Table Row extraction target in LlamaExtract solves the core problem: instead of trying to extract everything at once (where LLMs get overwhelmed),

We launched a new API today to let you parse any Excel sheet in a structured table. Take a look at this example on core production costs 🌽: 1️⃣ The table is located at the center of the sheet with headers, footnotes, and a hierarchical column layout 2️⃣ We get back a structured

Announcing LlamaSheets in beta 🔥 Transform your messy spreadsheets into AI-ready data with our newest LlamaCloud API 📊 LlamaSheets (in beta) is a specialized API that automatically structures complex spreadsheets while preserving their semantic meaning and hierarchical

Have a LlamaAgent organize your study material: meet StudyLlama, a web app that uses LlamaAgents to help you organize and gather insights from your notes and papers! How it works: 📊 Create categories to classify your notes 📓 Upload your notes 🤖 Watch as LlamaClassify assigns

Extract data from table rows with precision using LlamaExtract's Table Row mode 📊 LlamaExtract now offers granular extraction capabilities that go beyond document-level processing, giving you powerful control over how your schema is applied: 🎯 Table row extraction applies

Not another PDF parser 📄 🤯? Here's why AI-powered document parsing is all the rave. AI document parsing has evolved beyond OCR to systems that truly understand documents like humans do 🧠 In our latest blog post, we explore what's changing the game: 📊 Zero-shot semantic