Knowledge catalogue
Three events, one award, a very respectable 4th place in hot sauce. Our SF Tech Week: → AI Demo Night w/ @ClickHouse + @artie_labs: @imaanxsultan won best demo → @matissemlk took 4th in the Blazel hot
Kemi posted on October 11, 2026 from San Francisco about attending events during SF Tech Week, highlighting the Agent Economy Gala where she praised @imaanxsultan and @llama_index. She noted a “silico
One of the biggest historical bottlenecks for training specialized models has been curating ground-truth. This is typically a very labor intensive process done with human supervision. Now frontier mod
'a corollary is that information about product quality will become more important and impactful' This feels like the next evolution of SEO/AEO that every product will try to game. Even if agents do th
Mistral OCR is on OpenDocRouter! For its price, it is decent over tables and reading order. It's also blazing fast at p50 1.8s per page We're constantly bringing in new models since OpenDocRouter laun
i'm pulling out my suit for this Huge shoutout to @imaanxsultan and everyone else for organizing! The Agent Economy Gala just maxed out at 400 guests Here’s a breakdown: - 203 founders ($1B+ raised co
The Agent Economy Gala just maxed out at 400 guests Here’s a breakdown: - 203 founders ($1B+ raised combined) - 67 founding operators - 58 investors - 23 creators - 295 guests building agent applicati
These days, you can pretty much solve any task by defining an eval and hillclimbing over it, instead of directly defining the deterministic/agentic workflow to solve it. The data provider companies' e
The team has announced the launch of **LlamaIndex**, an open‑source information‑retrieval library, with its main site listed at **llamaindex.ai**. The announcement was shared on Twitter by Imaan Sulta
What happens when a table contains tables? Usually, a mess. With LlamaParse, it comes out clean. Doc of the Week: Micron’s latest earnings deck. Even with two business units and same row names, LlamaP
LightOn OCR-3 is now available on OpenDocRouter, priced at 0.28 / 1m input and 1.40 / 1m output (it is ~$3.19 / 1k pages on ParseBench). We benchmarked it on ParseBench. It is on the pareto frontier f
Markdown has become a universal representation of information between humans and agents. It preserves core primitives needed to express structure (headings, lists), allows agents to read the informati
OpenDocRouter is basically OpenRouter for document OCR You can compare and use all your favorite OCR models under a single API / billing interface. They range from some of the lightweight/OSS models (
Claude Haiku 5.5 is now available on OpenDocRouter as one of the cheapest models for document parsing. It is roughly $1.2 / 1k pages and does quite well on tables and text reading order compared to ot
Imaan Sultan delivered a well-received presentation on the OpenAI‑style library @llama_index during an AI demo night hosted by @ClickHouseDB, filling the venue. The event's best demonstration award we
On October 7, 2026 Jerry Liu tweeted that “llamaparse” delivers consistently high document‑parsing quality across every dimension. The service can be accessed through cloud.llamaindex.ai. His post cur
OCR is the perfect example of a use case that has been dominated by legacy/brittle systems, and can be solved both accurately and cheaply by applying the right amount of agentic intelligence. A proper
OpenDocRouter is here! https://www.opendocrouter.ai/ Some time ago, I realized LlamaIndex was really good at benchmarking and applying nearly every model to document parsing (see: ParseBench). So, why
The power of OpenDocRouter is already working: Anthropic just dropped Haiku 5.5 and we already have initial benchmark results. I see pretty comparable results to Luna overal. Slightly better at tables
Today I’m excited to introduce OpenDocRouter - a unified API for document parsing with the latest frontier and open-weight models. There are a lot of VLMs and OCR models that can be used for document
Today we're announcing OpenDocRouter: every model for document parsing under one API. There are ~4,000 OCR models on Hugging Face, and the frontier labs ship a new one nearly every month. Whatever's b
You may ask why we’re doing this given that our main focus within LlamaParse (https://cloud.llamaindex.ai/) is building the best frontier models for document parsing and extraction. While we believe o
There's a party on Friday night that most of SF Tech Week will only hear about on Saturday. So, we made a vintage film to announce it. In the 1920s, inventions were rewriting everyday life and nobody
OCR is dead 🪦 Long live agentic OCR! Traditional OCR makes one pass and hands back whatever text it got. Tables get flattened, charts disappear, and multi-column layouts come out scrambled. Nothing ch
I agree that chatgpt/codex has the current best agent interface for deep work. - It unifies all my work (coding/knowledge work) in one interface. Toggling between chatgpt/codex doesn't have explicitly
We got extremely good at extracting a scanned from layer by layer 📋 - from printed fields, overlaid text, handwriting, and reviewer annotations. For instance, on an annotated permit, our Extract agent
Our new extraction agents are extremely good at reasoning over tables that span multiple pages sometimes a record starts on one page and finishes on the next. extremely common for real world docs (ins
Can your agent read the documents your business runs on? @jerryjliu0 on parsing, search & source citations. World’s Fair 2026 recording: https://www.youtube.com/watch?v=RQi7x-navxU Keep learning with
one of the most challenging tasks for frontier models is being able to extract thousands of values from extremely dense tables in documents. our new Extract v2.5 agents are able to get 93%-96%+ on lon
The BEA's new Q2 GDP-by-state was released, but the key data is entirely in an infographic, without a text-layer. LlamaParse's agentic parsing tier understands documents like this by default, and fait
Records that span multiple pages: 85.5% → 96.5%. That's where we most often see customers get stuck with existing tools. With citations on every value, the output is easy to trust. Great work from the
Today we’re introducing Extract v2.5 - a series of frontier agents tuned for document extraction. The agents (cost-effective, agentic, agentic plus) are tuned for value accuracy and grounding. Our ext
Turns out sometimes, you can just rebuild things. Congrats to the team on the launch! 🦙 🚀 Today we’re introducing Extract v2.5 - a series of frontier agents tuned for document extraction. The agents (
How many people show up on a Tuesday night to talk about document processing for AI agents? 🤔 In New York, enough to fill the room and start a waitlist. In San Francisco, almost 600. We were in both c
i kinda wish dots was a standalone app and not part of chatgpt. as it stands, it feels like a product feature (e.g. GPTs) and not a big, exciting new release. i might understand why they did it though
Last night, we hosted our monthly @daytonaio AI Builders Demo Night at the @WorkOS office in San Francisco! Great demos, conversations, and energy from the AI builder community. Huge thanks to @llama_
PDFs aren't built for machines: text shows up as glyphs with coordinates, tables as line segments instead of table structures. @jerryjliu0, CEO of LlamaIndex, digs into what that means for AI agents i
System one models are extremely useful for a variety of document tasks that require fast decisions: * orientation detection * language detection * classification * splitting We benchmarked Jev with ot
we comprehensively benchmarked gpt-6.1 sol on document OCR tasks. compared to gpt-6 sol from a week ago (!), we see a sizable increase in table parsing capabilities and reading order, which is pleasan
if this takes off, then i was 4 years too early 😭 https://x.com/jerryjliu0/status/1590192512639332353 only OGs remember gpt tree index The entire RAG industry is about to get cooked. Researchers devel
Parsing forms still trips up the latest frontier VLMs. A form isn't text on a page. It's a set of fields, grouped into sections, each tied to a specific box. That's why forms need purpose-built parsin
We built state-of-the-art models for reading forms 📋 Form documents have the following properties that trip up VLMs: ✅ They carry much more structure than can be represented in standard markdown. You
We comprehensively evaluated 16 recent frontier VLMs - including Opus 5.5 and GPT-6 Sol/Luna - on whether higher effort led to better document parsing performance. Higher effort typically leads to imp
A blank cell can change the meaning of a forecast. Four times a year, the Fed's 18 top policymakers each put their forecasts on paper: where growth, jobs, inflation, and interest rates are headed. Thi
blank cells in tables can mess up agent decision making many document OCR tools struggle with reading multiple blank cells in a document and cause values to be shifted from the original column and row
building in the agent space? this is your room at SF @Techweek_. think modern gatsby: black tie, red carpet, cocktails, live jazz & art deco glamour. 300+ founders, founding operators & investors acro
confidence scores only matter if they help you decide what to automate. for document extraction, that usually means knowing how much work you can safely accept at a given precision target. in our late
predicting model uncertainty is a hard problem. perfectly 'calibrated' confidence scores are exact probability values on whether the output is correct. this is extremely important for agentic decision
sorry to every other sf tech week host in advance, but we may have gotten carried away planning our event... we're about to host the biggest and most lavish black-tie gala sf tech has ever seen. live
This is a fantastic blog post from our research team on the importance of calibrated confidence scores. Here it's in the context of document extraction, it's also extremely important for more general
we've built the world's most advanced engine for document extraction over complex documents the video below shows an overview of LlamaExtract Agentic Plus in action. long tables, giant forms, calibrat
Excited for next Tuesday, Sept 29, and our monthly @daytonaio AI Builders Demo Night in SF! We’re hosting at @WorkOS SF Office in partnership with @llama_index. Join us for an evening of great demos,
holy fuck it's christmas Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe. GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, bringing much of its strengths into faster and more
Opus 5.5 is the best frontier model for parsing tables in PDFs. We ran it through ParseBench, and it scored 93.9%, a 7%+ increase over Opus 5, and beating Fable/Gemini/Astra. It's comparable to LlamaP
The fastest PDF-to-Markdown parser just got faster. ⚡️ With LiteParse v2.14.6, text-based PDFs parse about 25% faster. Across realistic documents, LiteParse processed pages at 2.8ms/page and 1.5× fast
Document classification and splitting idea using @typesafeai Jev based on LiteParse, and LlamaParse. Classify: categorize probabilities, and review flags. Measure: separate OCR and decision timing, pr
Grounded Confidence is here for Extract! 🦙 When your agents and workflows depend on extracted data, you need to know how accurate that data is. We’ve added confidence scores to give you a better read
with jev, everyone is understanding the importance of calibrated confidence scores for discrete decision making we've taken that approach one-step further and created grounded confidence scores for ge
Doc + Jev => DocJev @llama_index 团队最新开源文档分类与拆分工具 DocJev，给它一个 PDF/DOCX/PPTX 和一份用自然语言写的类别规则，它可以告诉你这份文档属于哪个类别，或者把一份“文件包”按边界拆成若干子文档并给出各自页码范围。 开源地址：https://github.com/jerryjliu/docjev 核心架构：解析与决策分离 1. 解析层（O
Introducing DocJev - a lightning-fast OSS library for document classification and splitting with jev ⚡️ Give a document alongside some natural language category rules. Jev will predict the document ca