Enterprise organizations collect massive volumes of unstructured data, such as images, handwritten text, documents, and more. They also still capture much of this data through manual processes. The way to leverage this for business insight is to digitize that data. One of the biggest challenges with digitizing the output of these manual processes is transforming this unstructured data into something that can actually deliver actionable insights.
Artificial Intelligence is the new mining tool to extract business insight gold from the more complex and more abstract unstructured data assets. To help quickly and efficiently create these new AI applications to mine unstructured data, Cloudera is excited to introduce a new addition to our Accelerator for Machine Learning Projects (AMPs), easy-to-use AI quick starters, based on Anthropic Claude, a Large Language Model (LLM) that supports the extraction and manipulation of information from images. Claude 3 goes beyond traditional Optical Character Recognition (OCR) with advanced reasoning capabilities that enable users to specify exactly what information they need from an image– whether it’s converting handwritten notes into text or pulling data from dense, complicated forms.
Unlike Other OCR systems, which can often miss context or require multiple steps to clean the data, Claude 3 enables customers to perform complex document understanding tasks directly. The result is a powerful tool for businesses that need to quickly digitize, analyze, and extract machine usable data from unstructured visual inputs.
Searching and retrieving information from unstructured data is critical for companies who want to quickly and accurately digitize manual, time-consuming administrative tasks. This AMP makes it possible to quickly deliver a production-ready model that is fine-tuned with organizational data and context specific to each individual use case.
Some possible use cases for this AMP include:
Transcribing Typed Text: Quickly extract digital text from scanned documents, PDFs, or printouts, supporting efficient document digitization.
Transcribing Handwritten Text: Convert handwritten notes into machine-readable text. This is ideal for digitizing personal notes, historical records, and even legal documents.
Transcribing Forms: Extract data from structured forms while preserving the organization and layout, automating data entry processes.
Complex Document QA: Ask context-specific questions about documents, extracting relevant answers from even the most complicated forms and formats.
Data Transformation: Transform unstructured image content into JSON format, making it easy to integrate image-based data into structured databases and workflows.
User-Defined Prompts: For advanced users, this AMP also provides the flexibility to create custom prompts that cater to niche or highly specialized use cases involving image data.
Get Started Today
Getting started with this AMP is as simple as clicking a button. You can launch it from the AMP catalog within your Cloudera AI (Formerly Cloudera Machine Learning) workspace, or start a new project with the repository URL. For more information on requirements and for more detailed instructions on how to get started, visit our guide on GitHub.
