LandingAI Team
October 3, 2025
The messy reality of enterprise documents has long been a wrestling match. Contracts arrive with embedded signatures, invoices are scanned at awkward angles and compliance files are littered with checkboxes, seals and stamps. While large language models within enterprise workflows have proved to be powerful and productive, they often stumble when faced with this kind of complexity.
Ava Xia
October 2, 2025
Today we are sharing a powerful solution for a high-volume document extraction pipeline which lands data into Snowflake. Built specifically for Snowflake Data Engineers, the GitHub repo provides an end-to-end workflow which provides performance at scale: cost‑efficient document processing in the cloud and streaming ingestion into Snowflake. This agentic document extraction workflow offers: We’ll walk […]
LandingAI
September 30, 2025
LandingAI, a pioneer in agentic vision AI technologies, today announced its significantly upgraded version of Agentic Document Extraction (ADE) which will use a new model, Document Pre-trained transformer-2, to accurately extract information even from complex documents, to better inform organizational decision making.
LandingAI
September 30, 2025
When we first launched Agentic Document Extraction (ADE), our focus was on breaking documents into agentic chunks: text, tables, figures. That was already a step forward from monolithic OCR, because it gave developers structured building blocks. But in the real world, documents aren’t that simple. A financial report may include tables, signatures, stamps, and logos […]
Ankit Khare
September 24, 2025
Document processing has advanced through several waves: OCR for digitization, statistical and early machine learning methods for structure, and LLMs for reasoning. Each step solved part of the problem but left gaps in consistency, scale, or traceability. This blog explores that evolution and introduces Agentic Document Extraction (ADE), a Visual AI-first, schema-driven approach built to deliver reliable and auditable results for real-world enterprises.
LandingAI Team
September 17, 2025
Strategic investment secures ABB’s use of LandingAI’s vision AI capabilities, such as LandingLens™, for robot AI vision applications
Pre-trained models, smart data workflows and no-code tools reduce training time by 80% and accelerate deployment in fast-moving sectors including logistics, healthcare, and food & beverage
Ava Xia
September 16, 2025
This tutorial goes step by step into the process of building a MCP Server for Intelligent Document Processing using LandingAI's Agentic Document Extraction
Reasoning models are good at thinking over text but documents aren’t just text. PDFs are visual artifacts—tables, columns, captions, footnotes—and flattening them erases structure and invites errors. This post shows how Model Context Protocol (MCP) lets an agent discover and call LandingAI’s Agentic Document Extraction (ADE) for layout-aware parsing.
Ankit Khare
August 28, 2025
Turn complex lab reports into clean, structured data ready for analysis and dashboards using zero-shot parsing and schema-guided extraction