Best AI tools for< Process Ocr >

Receipt OCR API by ReceiptUp is an advanced tool that leverages OCR and AI technology to extract structured data from receipt and invoice images. The API offers high accuracy and multilingual support, making it ideal for businesses worldwide to streamline financial operations. With features like multilingual support, high accuracy, support for multiple formats, accounting downloads, and affordability, Receipt OCR API is a powerful tool for efficient receipt management and data extraction.

Ocrolus is an intelligent document automation software that leverages AI-driven document processing automation with Human-in-the-Loop. It offers capabilities such as classifying, capturing, detecting, and analyzing documents, with use cases in cash flow, income, address, employment, and identity verification. Ocrolus caters to various industries like small business lending, mortgage, consumer finance, and multifamily housing. The platform provides resources for developers, including guides on income verification, fraud detection, and business process automation. Users can explore the API to build innovative customer experiences and make faster and more accurate financial decisions.

ImageTextify is a free, AI-powered OCR tool that enables users to extract text from images, PDFs, and handwritten notes with high accuracy and efficiency. The tool offers a wide range of features, including multi-format support, batch processing, and a mobile-friendly interface. ImageTextify is designed to cater to both personal and professional needs, providing a seamless solution for converting images to text. With a focus on privacy, speed, and support for multiple languages and formats, ImageTextify stands out as a reliable and user-friendly OCR tool.

VoiceGPT is an Android app that provides a voice-based interface to interact with AI language models like ChatGPT, Bing AI, and Bard. It offers features such as unlimited free messages, voice input and output in 67+ languages, a floating bubble for easy switching between apps, OCR text recognition, code execution, image generation with DALL-E 2, and support for ChatGPT Plus accounts. VoiceGPT is designed to be accessible for users with visual impairments, dyslexia, or other conditions, and it can be set as the default assistant to be activated hands-free with a custom hotword.

Base64.ai is an AI-powered document intelligence platform that offers an all-in-one solution to bring AI into document-based workflows. It provides capabilities for complex document processing, workflow automation, AI agents, and data intelligence. The platform uses multi-modal AI to ingest data from various document types, images, and multimedia, and offers pre-trained deep learning models for fast setup without the need for model training. Base64.ai helps automate business decisions through AI agents and Large Action Models, generating charts and reports based on insights from multiple sources. It aims to eliminate manual document processing and outdated text extraction systems, enabling organizations to achieve new levels of efficiency, accuracy, and digital transformation.

GetSearchablePDF is an online tool that allows users to convert scanned or image-based PDF documents into searchable PDFs. With its advanced OCR (Optical Character Recognition) technology, the tool accurately extracts text from images, making the resulting PDFs easy to search, edit, and share. The process is simple and straightforward: users simply connect their Dropbox or OneDrive account, drag and drop their PDF files into the designated folder, and the tool automatically converts them into searchable PDFs.

Shufti Pro is an award-winning global identity verification platform that provides businesses with a suite of tools to verify the identities of their customers. The platform uses artificial intelligence (AI) to automate the identity verification process, making it faster, more accurate, and more secure. Shufti Pro's solutions are used by businesses in a variety of industries, including banking, fintech, crypto, forex, gaming, insurance, education, healthcare, e-commerce, and travel.

The AI Bank Statement Converter is an industry-leading tool designed for accountants and bookkeepers to extract data from financial documents using artificial intelligence technology. It offers features such as automated data extraction, integration with accounting software, enhanced security, streamlined workflow, and multi-format conversion capabilities. The tool revolutionizes financial document processing by providing high-precision data extraction, tailored for accounting businesses, and ensuring data security through bank-level encryption. It also offers Intelligent Document Processing (IDP) using AI and machine learning techniques to process structured, semi-structured, and unstructured documents.

Veryfi is an OCR API tool for invoice and receipt data extraction. It offers fast, accurate, and secure document capture and data extraction on any type of document. Veryfi empowers users to process documents efficiently, automate manual data entry, and implement AI into various business processes. The tool is designed to streamline workflows, enhance accuracy, and unlock new levels of efficiency across industries such as finance, insurance, and more.

Picture to Text Converter is an online tool that uses Optical Character Recognition (OCR) technology to extract text from images. It can process various image formats like JPG, PNG, GIF, scanned documents (PDFs), and even photos taken with your phone's camera. The extracted text can be copied to the clipboard or downloaded as a TXT file. Picture to Text Converter is free to use and does not require any registration or installation. It is a convenient and efficient way to convert images into editable text.

Procys is a document processing platform powered by AI that offers automated document processing solutions. It provides features such as a self-learning engine, seamless integration with ERP systems, OCR API powered by AI, customized data extraction, and AI autosplit for automatic document splitting. Procys helps with tasks like invoice OCR, ID card OCR, receipt OCR, and account payable automation. The platform aims to streamline document workflows, eliminate manual processes, save time, reduce errors, and ensure compliance for businesses.

Wisedocs is an AI-powered platform that specializes in medical record reviews, summaries, and insights for claims processing. The platform offers intelligent features such as medical chronologies, workflows, deduplication, intelligent OCR, and insights summaries. Wisedocs streamlines the process of reviewing medical records for insurance, legal, and independent medical evaluation firms, providing speed, accuracy, and efficiency in claims processing. The platform automates tasks that were previously laborious and error-prone, making it a valuable tool for industries dealing with complex medical records.

RecordMe is an AI-powered automated accounting and bookkeeping platform that offers fully automated data extraction, real-time access to business records, and streamlined invoice processing. The platform leverages OCR technology to extract and categorize accounting data efficiently, providing users with valuable data insights. RecordMe aims to maximize operational efficiency, eliminate manual data entry processes, and empower businesses to automate accounting and bookkeeping through a simple drag-and-drop process.

Mendel AI is an advanced clinical AI tool that deciphers clinical data with clinician-like logic. It offers a fully integrated suite of clinical-specific data processing products, combining OCR, de-identification, and clinical reasoning to interpret medical records. Users can ask questions in plain English and receive accurate answers from health records in seconds. Mendel's technology goes beyond traditional AI by understanding patient-level data and ensuring consistency and explainability of results in healthcare.

FormX.ai is an AI-powered data extraction and conversion tool that automates the process of extracting data from physical documents and converting it into digital formats. It supports a wide range of document types, including invoices, receipts, purchase orders, bank statements, contracts, HR forms, shipping orders, loyalty member applications, annual reports, business certificates, personnel licenses, and more. FormX.ai's pre-configured data extraction models and effortless API integration make it easy for businesses to integrate data extraction into their existing systems and workflows. With FormX.ai, businesses can save time and money on manual data entry and improve the accuracy and efficiency of their data processing.

Honeybear.ai is an AI tool designed to simplify document reading tasks. It utilizes advanced algorithms to extract and analyze text from various documents, making it easier for users to access and comprehend information. With Honeybear.ai, users can streamline their document processing workflows and enhance productivity.

PicNotes is a web-based image-to-text converter that can convert messy images into summaries, text, or explanations. It supports handwritten papers, medical reports, and other types of images. The tool is easy to use: simply upload an image and choose the desired output format. PicNotes will then process the image and return the results within seconds.

ReadyRedact is a cloud-based, AI-powered document redaction software that helps businesses and organizations permanently remove confidential data from documents. It uses advanced pixel-to-pixel replacement technology to ensure that sensitive information is completely removed, adding a higher level of security to files and peace of mind to regulatory compliance processes. ReadyRedact automates and streamlines the redaction process, eliminating the risk of identity theft, fraud, and litigation due to data leaks or outright theft.

Hailo is a leading provider of top-performing edge AI processors for various edge devices, offering generative AI accelerators, AI vision processors, and AI accelerators. The company's technology enables high-performance deep learning applications on edge devices, catering to industries such as automotive, security, industrial automation, retail, and personal computing.

Graphcore is a cloud-based platform that accelerates machine learning processes by harnessing the power of IPU-powered generative AI. It offers cloud services, pre-trained models, optimized inference engines, and APIs to streamline operations and bring intelligence to enterprise applications. With Graphcore, users can build and deploy AI-native products and platforms using the latest AI technologies such as LLMs, NLP, and Computer Vision.

The text-extract-api is a powerful tool that allows users to convert images, PDFs, or Office documents to Markdown text or JSON structured documents with high accuracy. It is built using FastAPI and utilizes Celery for asynchronous task processing, with Redis for caching OCR results. The tool provides features such as PDF/Office to Markdown and JSON conversion, improving OCR results with LLama, removing Personally Identifiable Information from documents, distributed queue processing, caching using Redis, switchable storage strategies, and a CLI tool for task management. Users can run the tool locally or on cloud services, with support for GPU processing. The tool also offers an online demo for testing purposes.

MouseTooltipTranslator is a Chrome extension that allows users to translate any text on a webpage by simply hovering over it. It supports both Google Translate and Bing Translate, and can also be used to listen to the pronunciation of words and phrases. Additionally, the extension can be used to translate text in input boxes and highlighted text, and to display translated tooltips for PDFs and YouTube videos. It also supports OCR, allowing users to translate text in images by holding down the left shift key and hovering over the image.

The Mistral Python Client is a tool inspired by cohere-python that allows users to interact with the Mistral AI API. It provides functionalities to access and utilize the AI capabilities offered by Mistral. Users can easily install the client using pip and manage dependencies using poetry. The client includes examples demonstrating how to use the API for various tasks, such as chat interactions. To get started, users need to obtain a Mistral API Key and set it as an environment variable. Overall, the Mistral Python Client simplifies the integration of Mistral AI services into Python applications.

Swift OCR is a powerful tool for extracting text from PDF files using OpenAI's GPT-4 Turbo with Vision model. It offers flexible input options, advanced OCR processing, performance optimizations, structured output, robust error handling, and scalable architecture. The tool ensures accurate text extraction, resilience against failures, and efficient handling of multiple requests.

The AI-Exchange Protocol (AIXP) is a communication standard designed to facilitate information and result exchange between artificial intelligence agents. It aims to enhance interoperability and collaboration among various AI systems by establishing a common framework for communication. AIXP includes components for communication, loop prevention, and task finalization, ensuring secure and efficient collaboration while avoiding infinite communication loops. The protocol defines access points, data formats, authentication, authorization, versioning, loop detection, status codes, error messages, and task completion verification. AIXP enables AI agents to collaborate seamlessly and complete tasks effectively, contributing to the overall efficiency and reliability of AI systems.

LARS is an application that enables users to run Large Language Models (LLMs) locally on their devices, upload their own documents, and engage in conversations where the LLM grounds its responses with the uploaded content. The application focuses on Retrieval Augmented Generation (RAG) to increase accuracy and reduce AI-generated inaccuracies. LARS provides advanced citations, supports various file formats, allows follow-up questions, provides full chat history, and offers customization options for LLM settings. Users can force enable or disable RAG, change system prompts, and tweak advanced LLM settings. The application also supports GPU-accelerated inferencing, multiple embedding models, and text extraction methods. LARS is open-source and aims to be the ultimate RAG-centric LLM application.

BionicGPT is an on-premise replacement for ChatGPT, offering the advantages of Generative AI while maintaining strict data confidentiality. BionicGPT can run on your laptop or scale into the data center.

The LLM-Aided OCR Project is an advanced system that enhances Optical Character Recognition (OCR) output by leveraging natural language processing techniques and large language models. It offers features like PDF to image conversion, OCR using Tesseract, error correction using LLMs, smart text chunking, markdown formatting, duplicate content removal, quality assessment, support for local and cloud-based LLMs, asynchronous processing, detailed logging, and GPU acceleration. The project provides detailed technical overview, text processing pipeline, LLM integration, token management, quality assessment, logging, configuration, and customization. It requires Python 3.12+, Tesseract OCR engine, PDF2Image library, PyTesseract, and optional OpenAI or Anthropic API support for cloud-based LLMs. The installation process involves setting up the project, installing dependencies, and configuring environment variables. Users can place a PDF file in the project directory, update input file path, and run the script to generate post-processed text. The project optimizes processing with concurrent processing, context preservation, and adaptive token management. Configuration settings include choosing between local or API-based LLMs, selecting API provider, specifying models, and setting context size for local LLMs. Output files include raw OCR output and LLM-corrected text. Limitations include performance dependency on LLM quality and time-consuming processing for large documents.

LLM Document OCR is a Node.js tool that utilizes GPT4 and Claude3 for OCR and data extraction. It converts PDFs into PNGs, crops white-space, cleans up JSON strings, and supports various image formats. Users can customize prompts for data extraction. The tool is sponsored by Mercoa, offering API for BillPay and Invoicing.

Rowfill is an open-source document processing platform designed for knowledge workers. It offers advanced AI capabilities to extract, analyze, and process data from complex documents, images, and PDFs. The platform features advanced OCR and processing functionalities, auto-schema generation, and custom actions for creating tailored workflows. It prioritizes privacy and security by supporting Local LLMs like Llama and Mistral, syncing with company data while maintaining privacy, and being open source with AGPLv3 licensing. Rowfill is a versatile tool that aims to streamline document processing tasks for users in various industries.

Sparrow is an innovative open-source solution for efficient data extraction and processing from various documents and images. It seamlessly handles forms, invoices, receipts, and other unstructured data sources. Sparrow stands out with its modular architecture, offering independent services and pipelines all optimized for robust performance. One of the critical functionalities of Sparrow - pluggable architecture. You can easily integrate and run data extraction pipelines using tools and frameworks like LlamaIndex, Haystack, or Unstructured. Sparrow enables local LLM data extraction pipelines through Ollama or Apple MLX. With Sparrow solution you get API, which helps to process and transform your data into structured output, ready to be integrated with custom workflows. Sparrow Agents - with Sparrow you can build independent LLM agents, and use API to invoke them from your system. **List of available agents:** * **llamaindex** - RAG pipeline with LlamaIndex for PDF processing * **vllamaindex** - RAG pipeline with LLamaIndex multimodal for image processing * **vprocessor** - RAG pipeline with OCR and LlamaIndex for image processing * **haystack** - RAG pipeline with Haystack for PDF processing * **fcall** - Function call pipeline * **unstructured-light** - RAG pipeline with Unstructured and LangChain, supports PDF and image processing * **unstructured** - RAG pipeline with Weaviate vector DB query, Unstructured and LangChain, supports PDF and image processing * **instructor** - RAG pipeline with Unstructured and Instructor libraries, supports PDF and image processing. Works great for JSON response generation

Panel Cleaner is a tool that uses machine learning to find text in images and generate masks to cover it up with high accuracy. It is designed to clean text bubbles without leaving artifacts, avoiding painting over non-text parts, and inpainting bubbles that can't be masked out. The tool offers various customization options, detailed analytics on the cleaning process, supports batch processing, and can run OCR on pages. It supports CUDA acceleration, multiple themes, and can handle bubbles on any solid grayscale background color. Panel Cleaner is aimed at saving time for cleaners by automating monotonous work and providing precise cleaning of text bubbles.

ExtractThinker is a library designed for extracting data from files and documents using Language Model Models (LLMs). It offers ORM-style interaction between files and LLMs, supporting multiple document loaders such as Tesseract OCR, Azure Form Recognizer, AWS TextExtract, and Google Document AI. Users can customize extraction using contract definitions, process documents asynchronously, handle various document formats efficiently, and split and process documents. The project is inspired by the LangChain ecosystem and focuses on Intelligent Document Processing (IDP) using LLMs to achieve high accuracy in document extraction tasks.

MiniCPM-V is a series of end-side multimodal LLMs designed for vision-language understanding. The models take image and text inputs to provide high-quality text outputs. The series includes models like MiniCPM-Llama3-V 2.5 with 8B parameters surpassing proprietary models, and MiniCPM-V 2.0, a lighter model with 2B parameters. The models support over 30 languages, efficient deployment on end-side devices, and have strong OCR capabilities. They achieve state-of-the-art performance on various benchmarks and prevent hallucinations in text generation. The models can process high-resolution images efficiently and support multilingual capabilities.

Generative Fusion Decoding (GFD) is a novel shallow fusion framework that integrates Large Language Models (LLMs) into multi-modal text recognition systems such as automatic speech recognition (ASR) and optical character recognition (OCR). GFD operates across mismatched token spaces of different models by mapping text token space to byte token space, enabling seamless fusion during the decoding process. It simplifies the complexity of aligning different model sample spaces, allows LLMs to correct errors in tandem with the recognition model, increases robustness in long-form speech recognition, and enables fusing recognition models deficient in Chinese text recognition with LLMs extensively trained on Chinese. GFD significantly improves performance in ASR and OCR tasks, offering a unified solution for leveraging existing pre-trained models through step-by-step fusion.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

LLMOCR is a tool that utilizes a local Large Language Model (LLM) to extract text from images. It offers a user-friendly GUI and supports GPU acceleration for faster inference. The tool is cross-platform, compatible with Windows, macOS ARM, and Linux. Users can prompt the LLM to process images in a customized way. The processing is done locally on the user's machine, ensuring data privacy and security. LLMOCR requires Python 3.8 or higher and KoboldCPP for installation and operation.

paperless-gpt is a tool designed to generate accurate and meaningful document titles and tags for paperless-ngx using Large Language Models (LLMs). It supports multiple LLM providers, including OpenAI and Ollama. With paperless-gpt, you can streamline your document management by automatically suggesting appropriate titles and tags based on the content of your scanned documents. The tool offers features like multiple LLM support, customizable prompts, easy integration with paperless-ngx, user-friendly interface for reviewing and applying suggestions, dockerized deployment, automatic document processing, and an experimental OCR feature.

The receipt-scanner repository is an AI-Powered Receipt and Invoice Scanner for Laravel that allows users to easily extract structured receipt data from images, PDFs, and emails within their Laravel application using OpenAI. It provides a light wrapper around OpenAI Chat and Completion endpoints, supports various input formats, and integrates with Textract for OCR functionality. Users can install the package via composer, publish configuration files, and use it to extract data from plain text, PDFs, images, Word documents, and web content. The scanned receipt data is parsed into a DTO structure with main classes like Receipt, Merchant, and LineItem.

This repository contains a collection of code samples that demonstrate how to use various Azure AI capabilities to process documents. The samples help engineering teams establish techniques with Azure AI Foundry, Azure OpenAI, Azure AI Document Intelligence, and Azure AI Language services to build solutions for extracting structured data, classifying, and analyzing documents. The techniques simplify custom model training, improve reliability in document processing, and simplify document processing workflows by providing reusable code and patterns that can be easily modified and evaluated for most use cases.

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Veterans Benefits Navigator (VBN) is a specialized chatbot designed to guide U.S. veterans through the complexities of VA benefits. It offers tailored, up-to-date information, locates nearest VA facilities, and ensures empathetic, confidential assistance for all benefit-related inquiries.