The Future of Document Processing with AI: How Unstract Simplifies AI Document Processing

Extract complex PDF, tables, and text data effortlessly and transform the way you handle unstructured documents.

In the ever-evolving digital landscape, businesses are tasked with handling large volumes of data across various formats. From legal contracts to financial statements, managing unstructured data poses a significant challenge. That’s where AI document processing comes in, revolutionizing the way we handle and interpret vast quantities of information.

One of the leading solutions in this space is Unstract, a powerful AI-based platform that simplifies document processing. This article explores the ins and outs of AI document processing and how Unstract can streamline your business’s document handling needs.

What is AI Document Processing?

AI document processing involves the use of artificial intelligence technologies like machine learning (ML) and natural language processing (NLP) to automate the extraction, classification, and analysis of data from documents. Traditional methods involve manual review, which is slow, error-prone, and resource-intensive. AI document processing, on the other hand, transforms unstructured data from various formats (PDFs, Word documents, images) into structured, machine-readable information, enabling businesses to process data faster, with greater accuracy, and at a lower cost.

Key Components of AI Document Processing:

1. Optical Character Recognition (OCR): OCR technology converts scanned images, PDFs, and other documents into machine-readable text. It is the first step in most AI document processing workflows.
2. Natural Language Processing (NLP): NLP helps the AI understand and interpret the text within a document, enabling it to extract relevant information and identify the relationships between different data points.
3. Machine Learning (ML): ML algorithms allow the AI to improve over time by learning from the data it processes. This ensures continuous improvement in accuracy and efficiency.
4. Data Structuring: After extracting text and data from documents, AI systems convert unstructured data into structured formats such as JSON or XML, making it easier to store, search, and analyze.
5. Automation and Integration: AI document processing tools can integrate with other business systems, enabling automated workflows for data entry, reporting, and decision-making. This eliminates the need for manual data transfer between systems.

Why AI Document Processing is a Game-Changer for Businesses

Handling large volumes of documents can be overwhelming, especially when accuracy is critical. In industries like finance, insurance, legal, and healthcare, timely and error-free document management is crucial. Here’s why AI document processing is transforming these industries:

1. Increased Efficiency and Speed: AI systems can process thousands of documents in a fraction of the time it would take a human team. Tasks like data extraction and classification are automated, speeding up document handling by orders of magnitude.
2. Accuracy and Reduced Errors: Manual data entry and document review are prone to errors. AI eliminates these risks by providing high accuracy in data extraction and validation, ensuring that critical business decisions are based on reliable information.
3. Cost Savings: By automating repetitive and resource-intensive tasks, businesses can significantly reduce operational costs. This includes savings on labor, time, and resources dedicated to document management.
4. Scalability: As businesses grow, so does their document volume. AI document processing tools can scale alongside your business, processing an increasing number of documents without compromising on performance.
5. Improved Compliance and Auditability: AI document processing helps businesses comply with regulatory requirements by maintaining accurate, auditable records. With AI, every action is traceable, and compliance checks can be automated.
6. Enhanced Customer Experience: Faster document processing allows businesses to serve customers more efficiently. In sectors like banking or insurance, this can significantly reduce the time taken to approve loans, process claims, or onboard new clients.

Achieving AI Document Processing with Unstract

Unstract is an AI-powered platform designed to simplify document processing for businesses of all sizes. Built to handle unstructured data, Unstract integrates cutting-edge AI technologies such as OCR to automate document processing with unparalleled efficiency and accuracy.

Here’s how Unstract achieves streamlined AI document processing:

1. End-to-End Automation:

Unstract offers a comprehensive platform that automates every stage of document processing. From ingestion to data extraction, and from transformation to export, Unstract handles it all. It doesn’t just stop at extracting text like traditional OCR tools — it takes the entire workflow into account.

Example: Imagine you receive a set of financial documents from a client. Instead of manually entering the data into your accounting software, Unstract’s platform automatically processes the documents, extracts the relevant financial details (such as invoices, balances, and customer information), and feeds it into your system as structured data.

2. Support for Unstructured Data:

One of the biggest pain points in document processing is dealing with unstructured data — text that doesn’t follow a predefined format. This could include invoices, contracts, or hand-written notes. Unstract leverages AI to intelligently process and structure unstructured data, allowing you to automate workflows even with complex document types.

3. Large Language Models (LLMs) for Enhanced Understanding:

Unstract integrates large language models (LLMs) like GPT-4 and Google’s Gemini Pro to enhance document understanding. These models are not only good at text generation but also excel at reasoning and following instructions. This means Unstract can interpret complex business documents, extract the right information, and even handle variations in document layouts.

Example Use Case: When processing legal contracts, the LLMs within Unstract can understand clauses, definitions, and legal language, ensuring that all relevant details are extracted and categorized correctly, regardless of the contract’s structure or format.

4. Custom Workflows and Prompt Studio:

Unstract’s platform includes Prompt Studio, a no-code tool that allows users to create custom workflows. You can easily upload documents, write prompts, and test document extraction across multiple documents in one place. This reduces the need for constant back-and-forth between different tools and increases productivity.

With Prompt Studio, businesses can create workflows that are specific to their document types, ensuring that the data extraction process is tailored to their needs. Once the prompts are refined, the workflows can be deployed as APIs or client applications.

5. Multi-LLM Accuracy Boost:

Unstract uses multiple LLMs for higher accuracy. It processes the document with one LLM, then cross-checks the result with another model. If the two models don’t agree, the data is flagged for review, ensuring that only accurate data gets through. This unique feature boosts accuracy levels to over 99%, which is critical for businesses that rely on precise data.

6. Cost-Effective Processing with Single Pass and Summary Extraction:

To save on processing costs, Unstract offers single-pass extraction and summary extraction. These features allow the platform to optimize token usage when interacting with language models. For instance, instead of sending multiple queries for different data points, Unstract intelligently combines these queries into a single request, reducing token consumption and saving on cost.

Practical Applications of Unstract in AI Document Processing

• Financial Services: Automates the extraction of data from bank statements, loan agreements, and financial reports, enabling faster and more accurate processing.
• Legal Industry: Processes complex legal texts, contracts, and agreements, allowing legal professionals to focus on analysis by automating data extraction.
• Healthcare: Handles unstructured medical documents like patient records and insurance claims, ensuring accurate and efficient data processing.
• Insurance: Automates the extraction of data from claims, policies, and forms, speeding up claim approvals and policy management.
• Real Estate: Extracts key information from property-related documents, simplifying tasks like processing purchase agreements and inspections.

Next, we’ll walk through a practical example using Unstract’s Prompt Studio to process a sample PDF. We’ll demonstrate how the platform automates data extraction from unstructured documents in real time, showing each step in action.

The first step is to log in and start using Unstract. You can begin with a 14-day free trial by visiting

https://unstract.com/start-for-free/

Unstract Cloud is a fully managed platform designed to eliminate manual processes involving unstructured documents by leveraging the power of LLMs (Large Language Models).

You can review the introductory documentation here:

Welcome to Unstract | Unstract Documentation

Prompt Studio and Unstract

We are focusing primarily on how to use Prompt Studio within Unstract to design prompts that can handle your queries effectively.

Once you’re logged in, you’ll see the main dashboard.

• On the left side, you can edit prompts.
• On the right side, you can upload your PDF or data files.

After uploading, you’ll be able to view the content of the files. The next step is to index these documents. On the next screen, click on Index, and the platform will automatically index the documents and store them in the default vector database (vectorDB).

By default, Unstract uses its standard vectorDB and LLM. However, you have the option to select your own preferred LLM and vectorDB.

After completing the indexing process, you can view the raw data. This is where you can see the raw text format, showcasing the power of llmwhisperer.

LLMs (Large Language Models) excel at extracting raw text while ignoring the layout, ensuring better understanding and improved output results. This feature highlights the efficiency and precision of LLMWhisper.

To learn more, visit LLMWhisperer | Unstract.

Prompt Studio: Custom Prompts for Extracting Desired Information

Heading: Employee Identification_Number Extraction

Below is the prompt to extract the employee identification number from the document:

#prompt example
extract the employee identification NUmber

Output in Yellow Indicates Correct Extraction

For example, the correct output for Employee Identification Number is: 789933.

You can compare this with the raw text provided below:

You can compare this with the raw text provided below.Similarly, you can extract other values by creating additional variables.For example, if you want to check whether a document has been signed, you can use the variable Signature_yes_or_no.

Additionally, you can check the output by clicking on Output Analyzer

This is how you should create the prompts and corresponding labels.

Below is the final output generated when we click on the combined output.

{
  "Identification_Number": 789933,
  "Signature_yes_or_no": "Yes, John Adams, Signature of officer, Date",
  "Revenue_years": "Prior Year Total Revenue: $23999\nCurrent Year Total Revenue: $33987",
  "Total_expenses": "Prior Year Total Expenses: $20000\nCurrent Year Total Expenses: $25000",
  "Executive_Compensation_and_Key_Personnel_Overview": "1. John Doe, Vice President, Officer and Director/Trustee, Reportable compensation: $2000\n2. Robert Mcfarlane, Director, Officer and Director/Trustee, Reportable compensation: $3000, Other compensation: $2500\n3. Susan, Director, Officer and Director/Trustee, Reportable compensation: $8933\n4. Dorothy Parker, Director, Officer and Director/Trustee, Reportable compensation: $3990, Other compensation: $1200\n5. Hernandez Dole, Vice President, Officer and Director/Trustee, Reportable compensation: $3900\n6. Patricia, Director, Officer and Director/Trustee, Reportable compensation: $9000\n7. Moses Kant, Manager, Reportable compensation: $3450\n8. John Smith, Executive Manager, Reportable compensation: $9007, Other compensation: $5600\n9. Simon Rogers, HR Manager, Reportable compensation: $3456\n10. Betty Smith, Operations Head, Reportable compensation: $2300\n11. Kathleen, Head of Operations, Reportable compensation: $6754\n12. Stephanie, Head of HR, Reportable compensation: $1200, Other compensation: $2133\n13. Nelson, Head of IT, Reportable compensation: $1300\n14. Charles, Head of Finance, Reportable compensation: $3200\n15. Kathleen, Security Head, Reportable compensation: $1670, Other compensation: $1200\n16. Stephanie, Security Operations, Reportable compensation: $1788, Other compensation: $1300\n17. Patrick, Finance Operations, Reportable compensation: $3500\n18. Phillips, Accounting Head, Reportable compensation: $3400\n19. Arthur, Designer, Reportable compensation: $2300"
}

Also we have option for single-pass extraction and summary extraction, which can be toggled on or off.

The advantage of this is to optimize processing costs, Unstract provides single-pass and summary extraction. These features help minimize token usage by combining multiple data queries into a single request when interacting with language models, reducing overall consumption and saving costs.

API Key Extraction:

To extract the API, follow these three steps:

1. Click on “Export as Tool”

This will save the tool in the workforce folder.

1. Now that we are exporting our API into the workflow, you’ll see the tool saved.

3. Your API will be ready in the API deployment section.

Why Choose Unstract for AI Document Processing?

1. Open-Source and No-Code Platform: Unstract is an open-source platform, offering flexibility for developers who want to integrate custom solutions. It also includes no-code features, making it accessible for non-technical users who want to automate document processing without writing code.
2. Seamless API Integration: Unstract can be easily integrated into existing workflows via APIs. This allows businesses to incorporate AI document processing into their current systems without the need for a complete overhaul.
3. Enterprise-Level Features: For larger organizations, Unstract offers enterprise-grade features like data privacy, GDPR compliance, and high scalability, ensuring that it meets the demands of complex business environments.
4. Support for Handwritten Documents and Complex Layouts: Unstract’s powerful OCR engine can handle not just printed documents but also scanned images and handwritten text. This makes it a versatile tool for businesses dealing with varied document types.

Conclusion: AI Document Processing Made Easy with Unstract

AI document processing is transforming the way businesses handle data. With tools like Unstract, organizations can automate document workflows, reduce errors, save costs, and improve efficiency. Whether you are a small business looking to streamline operations or a large enterprise in need of robust, scalable solutions, Unstract provides the flexibility, power, and ease-of-use to meet your needs. Its open-source nature, no-code options, seamless API integration, and advanced OCR capabilities make it the ideal choice for modern document processing.