Hi, this is Adrian at Llama Index. Today we're going to demo customizing our extraction review template. Um, for our specific data, the data that we're going to extract from is receipts and invoices.These can be kind of messy, hard to read, and they have lots of different line items that need to be extracted, taxes. Uh, I've started working on a schema here. We'll make use of that.Um, a lot of the work here is actually in the schema development. So, this template's going to free you up to focus on the real ...

Hi, this is Adrian at Llama Index. Today we're going to demo customizing our extraction review template. Um, for our specific data, the data that we're going to extract from is receipts and invoices.These can be kind of messy, hard to read, and they have lots of different line items that need to be extracted, taxes. Uh, I've started working on a schema here. We'll make use of that.Um, a lot of the work here is actually in the schema development. So, this template's going to free you up to focus on the real ...

Today we're opening Llama agents to early access. And in this video I'm going to walk you through how you can get started. Um at the end of the video, what I want to achieve is an agent that's been deployed to our Llama Cloud project.Um and to start off with that, what we first need to install is Llama Control. So you can start with UV install Llama control. I already have it.And once you have that installed, you can say llamactl in it, which will spin up a CLI that allows us to decide what kind of llama ag ...

So at a high level, the agents product is designed to allow our customers to quickly build, deploy, and scale document workflows while using Llama Cloud under the hood. Uh the goal here is to allow them to take things from prototype to production at a much faster rate while also allowing multiple deployment types. Cool.So the first thing we're going to do is download llama control and then we can do llama control in it. And we're going to see different templates here. And we're going to continue to add more ...

[Music] The world runs on documents. I'm Jerry Lou, co-founder and CEO of Llama Index. Over the past 2 years, I've watched generative AI applications mature.From early RAG demos with a single question box to orchestrated multi-step contextaware agents. At Llama Index, we've been at the center of that journey. From jumpstarting rag with five lines of code to a multi-agent framework powering millions of production workflows with over 4 million downloads a month to the millions of AI builders who've been with ...

We all talk about AI but without data uh none of this is going to work. My name is Swami Chandra Shakaran. I'm a partner at uh KPMG.I lead the AI and data labs for the firm both here in the US and globally. We are a professional services firm. Tax audit advisory are three broad lines of business when it comes to making these language models understand the context that you're dealing with.Having the right data for AI, having the right data that AI needs to do inferencing on is going to be very critical and a ...

Product Overview - Lava Index introduces Classify, a beta feature for document classification [1] - Classify uses descriptions to classify documents, streamlining workflows with multiple document types [2] - The service saves parsing time by setting a maximum of five pages to determine document type [4] Functionality and Use Cases - Classify supports built-in templates like résumés and custom rules for documents like 10K filings (annual financial regulatory reports) [3][4] - Users can upload files and the system classifies them, showing examples of correctly classifying résumés and 10K filings [5] - The tool is accessible via UI for testing and via script for production use [6] Technical Implementation - Implementation requires installing the Llama Cloud services package and setting up a Llama Cloud client with an API key, project ID, and organization ID [6] - Classification by file path provides results with confidence scores and natural language reasoning for the classification [7][8] Key Metrics - The system provides a confidence score, for example, 95% confidence in classifying a document as a 10K report [8]

AI Implementation & Business Impact - Seix, a global building material company, utilizes AI to enhance maintenance, supply chain optimization, smart operations, health and safety, and commercial efforts [1] - AI helps Seix's salespeople improve customer engagement [1] - Data ingestion process improved significantly, reducing time from approximately 3 weeks to less than a day with Lama Cloud [2] - The company is experiencing real results, insights, and measurable gains from AI implementation [2] Strategy & Recommendations - It's recommended to prioritize business problems over technology when implementing AI [2] - Choosing a framework with a strong community is crucial for staying updated and collaborating with others [2] - The goal should be to drive meaningful improvements and "move the needle" [2]

Since we started using Llama Cloud, our data ingestion process uh moved from taking around 3 weeks up to less than a day. My name is Daniel Garcia Zapata. I'm a senior data scientist at Se, a global building material company, one of the largest rhythmics producers in the world.We use AI to improve our maintenance, supply chain optimization, smart operations, health and safety, and for commercial efforts, we use it to uh help our salespeople improve uh their engagement with our customers. We didn't have a st ...

Workflow Example: https://docs.cloud.llamaindex.ai/llamaextract/examples/extract_data_with_citations Notebook: https://colab.research.google.com/drive/1JyUvSwxOwc349cYrGIbALD8C7NI2pmU1 Financial services are overloaded with complex, unstructured documents—10-Ks packed with nested tables, earnings reports combining charts and text, and regulatory filings in inconsistent formats. Traditional OCR and extraction tools fall short when faced with these real-world, multimodal documents. In this webinar, you’ll lea ...