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Introducing the first in our Parsed by LlamaParse series. We're outlining the stakes of 'getting parsing wrong' in consequential documents. We’re starting with the U.S. Energy Information Administrati

Static embeddings offer unmatched throughput, but they also suffer from accuracy loss compared to traditional embedding models. Can we make them better for retrieval? We tried several things: ✅️ raw m

Every extraction API demos well on a clean invoice. But what about the scanned form, the nested table, the 40-page financial report with merged headers? We tested 14 frontier systems to find out. Extr

Most document extraction APIs can't tell you where a value came from. For ExtractBench, we scored grounding strictly: a field only counts if the value AND its citation are correct, word-level box at I

spotlighting the partners and speakers joining Summer Signal '26 🦙@llama_index joins as an agentic partner. They'll be on stage talking through document parsing and analysis in agentic workflows. Regi

You shouldn't need a vision model to know your PDF has checkboxes. LiteParse can now pull structured data directly from your PDFs: form field values, checkbox states, annotations, embedded images, vec

Agentic retrieval is changing the way retrieval-augmented applications are built, especially in domains like legal and fintech, where agents need to autonomously navigate large, evolving knowledge bas

Semantic search alone doesn't cut it. Neither does brute-force grep. Agents need both. Today we're shipping the Retrieval Harness in LlamaParse Index: semantic search, server-side grep, and file-level

LlamaParse now parses HEIC files natively 🎉 . HEIC is Apple's default image format, so it shows up all over enterprise file systems. Photos of whiteboards, scanned docs, receipts snapped on an iPhone.

New in LlamaParse: Latency Metrics is now live. For every Parse, Extract, and Classify job, you can now get a full latency breakdown. All broken down by tier. ⏱ Queue time ⚡Processing time 📊 Total lat

Financial analysts spend ~70% of their time pulling numbers out of PDFs. We built a demo agent that ingests SEC filings and answers questions with exact citations highlighted on the original PDF page.

🚀 The team at @Google just released the Agents API, a service for building and running custom agents inside a sandboxed Linux environment, and we built a template that gives these agents access to Lla

We're live at @googleio! Thanks, @OfficialLoganK for the shoutout in the developer keynote. Lots of exciting features comining to the @GeminiApp API🔥 and we're exciting to provide the document infrast

Need document parsing that stays fully local and private? 👀 Meet liteparse-server, a self-hostable, open-source HTTP server for parsing documents and generating screenshots from PDFs, Office files, an

LiteParse hit 4.3K+ GitHub stars in a few weeks. Today it officially joins the LlamaIndex ecosystem, with its own page at http://www.llamaindex.ai/liteparse?utm_medium=socials&utm_source=twitter&utm_c