š 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 LlamaParse / LiteParse, enabling them to process unstructured documents https://t.co/cS6Ydyt9Kt
LiteParse v2.1 is here, and its bringing the fastest markdown output possible. In this release, we are fulfilling our top request: markdown output. But in the spirit of "lite"-ness, we are doing this completely LLM-free and fast. Not only is it fast, it also beats all other https://t.co/bdnSdNsMhA
We're launching LlamaAgents Builder today: a new way to build document processing agents š„ Instead of choosing between inflexible no-code tools or writing everything from scratch, just describe what you need in natural language. Our builder generates actual Workflow code that https://t.co/I0coPYnDL9
Let's talk content faithfulness. Four days ago, we launched ParseBench, the first document OCR benchmark for AI agents. Its most fundamental metric asks: did the parser capture all the text, in order, without making things up? We grade three failure modes with 167K+ rule-based https://t.co/7vgxG4OFqS
We just built a Private Equity Assistant with LlamaAgents and the newly released LlamaCloud SDK. It can: š Turn portfolio spreadsheets into structured, LLM-ready data with LlamaSheets š Classify investor decks and extract key details with LlamaClassify and LlamaExtract š¤ https://t.co/udycH9Fnng
