Author name: Shubhankar Biswas

Back to Blog Table of contents On this page Best LLM Models for Document Processing in 2025 Home › Blog › Algodocs › Best LLM Models for Document Processing in 2025 Categories Algodocs By Shubhankar Biswas Published September 1, 2025, 07:11 Updated July 21, 2026, 05:34   Modern businesses run on data. And when it comes to extracting valuable data from PDFs, scanned images, handwritten notes, etc., the task becomes harder. However, with the evolution of technologies like OCR, LLM and intelligent document processing, this task has become faster and more accurate. LLM models for document processing and automation has not only improved the quality of data extracted but also streamlined the entire process with your existing business tools. While enterprise-level data extraction solutions already exist, there’s one new technology that is also emerging and gaining attention in document processing: AI (Artificial Intelligence) and LLMs (Large Language Models). One of the most popular LLMs is ChatGPT, developed by OpenAI, which has inspired several other companies to launch their own LLMs for public use. But when it comes to document processing and extracting data from various formats such as PDFs, scanned images, handwritten notes, invoices, bills, or even personal notes, do these models actually stand up to the hype? In this blog, we’ll talk about the top commercially available LLM models you can use for document processing, the types of documents they support, and what kind of data they can extract. We’ll also go through the pros and cons of using LLMs for document processing and how they compare with OCR and IDP technologies. But before we jump to the best LLMs for document processing, let’s understand what an LLM is. What is an LLM model? An LLM, or Large Language Model, is an artificial intelligence program that is trained on huge datasets to generate text, create images, write code, and automate various tasks. LLMs are built using neural networks that learn patterns in language and data to understand, predict, and perform specific actions. In simple terms, you can think of LLMs as bots that can automate tasks like document processing and data extraction. However, they do have limitations and are not always reliable when it comes to complex or robust data extraction tasks, which we’ll cover in detail in this blog. What is an LLM for Document Processing? LLM for document processing refers to using large language models to extract data from various types of documents such as invoice, bills, insurance documents, purchase orders etc.  There are no LLMs tools built specifically for document processing, but several commercial models such as ChatGPT, Gemini and others have decent capabilities when it comes to extracting data from structured and basic document layouts. Why Use an LLM for Document Processing? LLMs available commercially can be useful when you want to extract data from simple document layouts or if the number of documents is small. For example, if you want to use a tool like ChatGPT, Claude, Gemini, or any other LLM platform available to the public, you can easily use them to perform light document processing tasks. They can help summarize PDF documents or extract specific data from the file. However, the main drawback is that LLMs don’t perform well when it comes to structured, unstructured, or complex documents. Compared to native document processing tools, LLMs offer limited features and flexibility. Top LLM Models for Document Processing in 2025 The answer depends on your specific requirements. Some of the most commonly available commercial LLM models for document processing include ChatGPT, Gemini, Copilot, Claude, Gork, and Llama 3. However, there are several other large language models in the market that can also be used for document processing. Let’s break down the features, pros, and cons of these LLM models for document processing. 1. OpenAI GPT-4 Turbo GPT-4 by OpenAI (ChatGPT) is one of the most widely used commercial LLMs for document processing. Its accuracy, speed, and ease of use make it a strong contender. OpenAI provides both free and paid versions depending on the type of data you want to extract from the document. Features: Supports multi-turn document interaction High accuracy in data extraction and summarization Can extract data from PDFs, scanned images (partially), and document files Pros: Easy to use Can be integrated with third-party platforms High data accuracy Cons: High computational cost Requires fine-tuning for domain-specific documents Limited capabilities with complex layouts and blurry images Pricing: $20/month, Free Plan Available 2. Claude 3 by Anthropic   Claude is another LLM that performs well when it comes to extracting data from documents. However, it is not as powerful as ChatGPT. It supports PDFs, DOCs, and TXT files but does not support data extraction from image-based PDFs. Features: Strong contextual understanding and summarization abilities Pros: Excellent for regulatory and compliance document analysis Cons: Limited file size (30MB) Tends to hallucinate with poor-quality or disorganized documents Pricing: $17/month, Free Trial Available 3. Google Gemini Pro Gemini by Google (formerly Bard) is another promising LLM you can use for document processing. Features: Integrates natively with Google Workspace Pros: Excellent multilingual support Can extract data from PDFs, DOCs, and scanned images Cons: Poor performance with complex PDFs or blurry image files Limited pricing transparency Vendor lock-in with Google Cloud Pricing: Starts at $22/month, Free Plan Available 4. LLaMA 3 by Meta LLaMA is an open-source LLM developed by Meta and released in 2023. It can handle PDFs, DOCs, and scanned files fairly well. However, it still struggles with complex layouts and blurry images. Features: Open-source with no usage restrictions Available in various model sizes Pros: Flexible deployment options Strong community support Cons: Not as robust as ChatGPT or Gemini May produce hallucinations during complex document tasks Pricing: Available for free How to Choose the Right LLM for Document Processing There are several LLMs that you can choose from. Make sure to check the following parameters: 1. Document Type and ComplexityStructured documents are easy for LLMs to extract data from. However, scanned PDFs and complex layouts like medical bills or invoices are still difficult. Most LLMs are

Back to Blog Table of contents On this page Cargo Manifest Data Extraction Using AI and Intelligent Document Processing: 2025 Guide Home › Blog › Algodocs › Cargo Manifest Data Extraction Using AI and Intelligent Document Processing: 2025 Guide Categories Algodocs By Shubhankar Biswas Published September 1, 2025, 06:55 Updated July 21, 2026, 03:58 In the fast-paced world of global trade and the logistics industry, efficiency and accuracy are key components for success. A widely used document in the logistics chain is the cargo manifest, which details the goods loaded onto a vessel. Extracting and automating valuable data from this document can help streamline operations, improve compliance, and ensure faster turnaround times for businesses. With advancements in AI, machine learning, and intelligent document processing (IDP) tools, organizations can now automate cargo manifest data extraction, which can greatly reduce manual labour, data errors, and improve document workflows. This article delves into how to efficiently extract data from a cargo manifest using modern technology, with a focus on cargo manifest data extraction and cargo manifest OCR. What is a Cargo Manifest? A cargo manifest is a comprehensive document that lists all the cargo on board a ship, aircraft, or vehicle. It includes detailed information such as the description of goods, quantity, weight, consignee, consignor, port of loading, and destination. This document plays a vital role in customs clearance, tracking shipments, and verifying the accuracy of goods transported. The cargo manifest is typically generated by the carrier or shipping company and is used by customs authorities, freight forwarders, and logistics professionals to ensure the legal and efficient movement of goods across borders. Difference Between Bill of Lading and Cargo Manifest People often mistake the bill of lading for the cargo manifest, but these two documents are different and serve different purposes. Bill of Lading (BOL): It’s a legal document between the shipper and carrier that outlines the terms of transport, serves as a receipt for goods, and can act as a title of ownership as well. It is usually specific to a particular shipment or container. Cargo Manifest: This is a summary document listing all shipments on a vessel. It provides a holistic view of the cargo and is used mainly for administrative, regulatory, and customs purposes. In essence, the bill of lading focuses on individual shipments, while the cargo manifest provides an aggregated view of the cargo. Here is the detailed explanation: Feature Bill of Lading (BoL) Cargo Manifest Primary Role Contract of carriage, receipt of goods, document of title (often negotiable). Consolidated inventory of all cargo on board for a specific voyage/trip. Issued By Carrier or its agent to the shipper. Carrier or its agent. Issued To Shipper (who then forwards it to the consignee). Customs, port authorities, vessel/aircraft operator. Scope Covers a specific consignment from one shipper to one consignee. Lists all consignments from all shippers on a single vessel/vehicle for a specific journey. Content Focus Detailed terms and conditions of carriage for a single shipment, description of goods, shipper/consignee details. Summary details of all shipments: BoL numbers, shipper/consignee (often summarized), marks, quantity, weight, port of loading/discharge. Legal Standing Legally binding contract, evidence of title. Primarily an administrative and customs declaration document. Use in Data Extraction BoL data extraction focuses on individual shipment details for contractual and title purposes. Cargo manifest data extraction focuses on a holistic view of all goods for customs, logistics planning, and reconciliation. Try Algodocs Data Extraction Tool To Automate Data Extraction From Cargo Manifest With 99.99% Accuracy. Sing Up For Free Account Today. Create Free Account What is Cargo Manifest Data Extraction? Cargo manifest data extraction means capturing relevant information such as MB/L number, shipment types, HB/L number, destination, product weights, and size from cargo manifest documents and converting it into structured, machine-readable formats. Traditionally, this extraction was done manually, requiring human operators to read through documents and input data into systems. But today, AI-driven tools, especially those employing cargo manifest OCR (Optical Character Recognition), can automate this process with remarkable accuracy. Challenges with Cargo Manifest Data Extraction Despite its numerous benefits, extracting data from cargo manifests poses several challenges such as: Document Variability: Cargo manifests can come in various formats and layouts, depending on the shipping company or region. This can create challenges for apps in data extraction and accuracy. Handwritten Entries: One common aspect of the shipping and cargo industry is that many documents contain handwritten notes or edits, which are difficult for standard OCR engines to interpret. Poor Document Quality: Scanned copies pose a great challenge because the scanned documents are often blurry, misaligned, or contain background noise. Data extraction tools find it difficult to extract data accurately. Multilingual Content: Global shipping and logistics involve documents in multiple languages, complicating the extraction process for data extraction tools. Regulatory Compliance: Ensuring extracted data meets regulatory standards and accuracy is essential for customs clearance. How to Choose a Reliable Tool for Cargo Manifest Data Extraction While there are many cargo manifest data extraction tools available in the market, selecting a reliable and accurate tool can be a challenging task. It needs to align with your business needs, should be accurate, and must integrate with your existing business apps and third-party platforms as well. Most importantly, consider how much ROI it delivers for every dollar you spend on the tool. Below are a few factors you need to take into consideration before picking a tool: Accuracy and Precision: Accuracy is the paramount factor for any data extraction tool. Be it a bill of lading, cargo manifest, or purchase order, a data extraction tool must offer high accuracy. Also, the tool must be able to extract data from scanned, blurry, and skewed documents. AI Capabilities: Traditional document extraction tools built on OCR technology miss many advanced features such as automation. AI-based document processing tools offer automation, third-party integration, and other benefits due to their vast ecosystem. Look for platforms using advanced AI and machine learning to improve extraction over time. Customization: The cargo manifest data extraction tool should come with customization features to make the process more