Cover image for post - Agentic Object Detection and Document Extraction with Landing.ai

Cover image for Agentic Object Detection and Document Extraction with Landing.ai

A hands-on exploration of two capabilities from Landing.ai, Andrew Ng’s computer vision startup: agentic object detection and agentic document extraction.

The object detection side skips model training entirely. Instead of labeling hundreds of images, you describe what you want to find in plain language and the model locates it. In testing, this worked on prompts like “coffee cup with a plant design” and “windows with room lights on” across real photos with high accuracy.

The document extraction side converts invoices, lab reports, and mixed-layout PDFs into clean markdown or JSON output. Processing that once took over two minutes now completes in about eight seconds, as noted in Andrew Ng’s announcement on X.

Read the full post (see related post button below) for screenshots, demo video, use cases, and notes on Landing.ai’s support responsiveness.

Additional comments:

Modern computer vision is undergoing a massive transformation with the arrival of agentic workflows. Landing.ai, founded by Andrew Ng, is leading this charge by simplifying complex visual tasks through natural language. Their platform eliminates the traditional burden of training custom models from scratch. Instead, users provide simple prompts to locate specific objects in real world scenarios. Whether identifying a coffee cup with a unique plant design or pinpointing windows illuminated in a nighttime building facade, the system delivers high accuracy without the need for massive labeled datasets.

Beyond basic detection, Landing.ai excels at complex document processing. The system seamlessly converts diverse inputs like invoices, lab reports, and complex PDF layouts into structured formats such as markdown or JSON. Performance benchmarks are equally impressive. Tasks that previously required over two minutes of manual or legacy processing now reach completion in roughly eight seconds. This efficiency creates significant value for teams needing to extract data at scale. The full post provides a deeper dive into these capabilities. Explore the provided demo videos, analyze real world use cases, and discover why the responsive support from the Landing.ai team remains a standout feature for enterprise developers.