Oct 13, 2026

Automating document work with Long-Horizon AI Agents at LlamaIndex

Jerry, CEO of LlamaIndex, argues that as AI agents move from answering questions to running long-lived workflows, documents become their most important context source. He walks through the evolution from simple RAG to agent harnesses, explains why PDFs are hard to parse, and presents the company's approach to OCR, extraction with grounding, and document search. He closes by outlining unsolved problems: agent-native document formats, in-place editing, versioning, distilling frontier workflows into cheaper models, and long-horizon background agents.

Oct 08, 2026

Why We Deleted Our MCP Server and Rebuilt It — Abhi Arya, Reducto

Abhi Arya from Reducto shares how the team went from a one-tool-per-endpoint MCP server that confidently built workflows nobody could explain to a design that makes uncertainty visible, asks instead of guessing, and improves itself through instrumentation. The talk centers on one question: who pays when the agent is wrong?

Sep 23, 2026

From Scratch to SOTA: Training a 3B State-Space Vision Model — Krishna Prasad Srinivasan, Sarvam

Sarvam introduces Vision India, a 3B parameter Vision Language Model achieving state-of-the-art in document AI for English and 22 Indian languages. It leverages a State Space Model (SSM) backbone for efficiency with long documents and a novel block-level OCR approach. A four-stage training curriculum, including advanced RL with verifiable rewards, and a robust data engine for low-resource languages underpin its superior performance, enabling the digitization of millions of pages for critical sectors.

Sep 16, 2026

Your Agreements Are a Database You Can't Query — Hiral Shah, Docusign & Sean Sodha, NVIDIA

The talk by Hiral Shah (DocuSign) and Sean Sodha (NVIDIA) addresses the critical challenge of extracting valuable, negotiated data from unstructured agreements, highlighting how generic AI models fail at complex tables. They introduce DocuSign's Intelligent Agreement Manager powered by NVIDIA's purpose-built, small-parameter NeMo Parse VLM, designed specifically for efficient and accurate table extraction, demonstrating 20x faster processing, lower cost, and its impact on unlocking billions in trapped enterprise data.

Jan 23, 2026

Fully Connected Tokyo: [Hands-on workshop] Automation of document workflows in financial industry

This workshop by Upstage demonstrates how to automate financial document workflows using a combination of their specialized Document AI (Document Parse) and Large Language Models (LLMs). The session covers building robust information extraction pipelines, addressing challenges like varied templates and data formatting, and implementing systematic evaluation using Weights & Biases Weave. It also presents real-world case studies from the insurance industry, showcasing significant improvements in efficiency and data utilization.