Best AI tools for< Customize Document Extraction >

Extracta.ai is an AI-powered platform that specializes in data extraction from unstructured documents. The platform offers automated document recognition and intelligent data automation services. Users can define custom templates for data extraction without the need for training. Extracta.ai can effortlessly extract data from various document types, such as CVs, invoices, and scanned images, providing structured data in seconds. The platform ensures secure data handling, GDPR compliance, and encrypted communication, making it a reliable solution for efficient document data extraction.

Procys is a document processing platform powered by AI solutions. It offers a self-learning engine for document processing, seamless integration with over 260 apps, OCR API powered by AI for optical character recognition, customized data extraction capabilities, and AI autosplit feature for automatic document splitting. Procys caters to various use cases such as invoice OCR, ID card OCR, receipt OCR, and account payable automation. It ensures data security as a top priority and simplifies the digitalization of documents in PDF, scan, or image format.

Otto is an AI-powered tool designed to streamline work processes by bringing reasoning to data. It allows users to define tables once and automate numerous tasks in minutes. With features like research capabilities, outbound message creation, and customizable columns, Otto enables users to work 10x faster by leveraging AI agents for parallel processing. The tool unlocks insights from various data sources, including websites, documents, and images, and offers an AI Assistant for contextual assistance. Otto aims to enhance productivity and efficiency by providing advanced data analysis and processing functionalities.

Lettria is a no-code AI platform for text that helps users turn unstructured text data into structured knowledge. It combines the best of Large Language Models (LLMs) and symbolic AI to overcome current limitations in knowledge extraction. Lettria offers a suite of APIs for text cleaning, text mining, text classification, and prompt engineering. It also provides a Knowledge Studio for building knowledge graphs and private GPT models. Lettria is trusted by large organizations such as AP-HP and Leroy Merlin to improve their data analysis and decision-making processes.

LeaseLens is a free AI-based lease abstraction software that simplifies the time-consuming and costly process of extracting relevant data points from real estate or commercial lease documents. The application uses award-winning machine learning technology to provide accurate lease abstracts in minutes, offering cost savings and efficient lease abstractions. Users can upload their leases, have the AI identify and extract the data, and view the abstract for free. LeaseLens also offers the option to export the abstract to Excel or Word for a small fee.

QueryPal is an AI chatbot application designed to provide better and faster answers for teams by leveraging AI technology trained on company documents. It helps in resolving repetitive questions instantly, ensuring accurate and contextualized results. The application allows users to create personalized AI chatbots for each team in minutes, with customization options for document access, chatbot admins, and tone. QueryPal offers unlimited connections to various platforms like Slack, Microsoft Teams, Google Drive, and more, making it a versatile tool for team communication and knowledge management.

FacePlugin is an ID verification and Biometric Authentication solution provider that utilizes advanced face recognition, face liveness detection, and ID document recognition technologies. The platform offers solutions for eKYC and ID verification needs, with features such as instant face recognition, enhanced face anti-spoofing technology, and robust identity document verification. FacePlugin aims to secure and streamline the authentication process for various industries and use cases, providing proprietary solutions, top-notch quality, and competitive pricing.

LegalPad.ai is an AI-powered smart drafting assistant that helps users draft legal documents efficiently and accurately. With a word limit of 5,000 words per day, users can access a wide range of sample templates for various legal agreements and documents. The platform offers features such as AI drafting wizard, Legalpad editor, saved drafts, set defaults, and sample templates for different types of agreements. Users can sign up to LegalPad.ai to get 10k credits and leverage the AI model GPT 4 for generating bare bones, standard, expanded & detailed, or elite & in-depth drafts in multiple languages.

Airstrip AI is an AI-powered legal platform designed for modern businesses to create bespoke legal documents quickly and efficiently. The platform utilizes AI technology to streamline the legal process, offering compliant and personalized documents tailored to specific requirements. Airstrip AI aims to provide cost-effective and risk-free legal solutions, empowering businesses without dedicated legal teams to focus on growth.

Solve Intelligence is an AI-powered platform designed to assist legal professionals in writing high-quality patents efficiently. The platform offers an in-browser document editor that leverages generative AI to streamline the patent drafting process. Solve Intelligence ensures complete confidentiality, state-of-the-art encryption, and industry-leading security certifications to protect user data. Trusted by IP teams worldwide, the platform allows users to customize AI drafting styles for different fields, clients, and regions, enhancing productivity and patent quality.

Podbrews is an AI-powered document-to-podcast conversion tool that harnesses the power of AI to transform written documents into engaging podcast-style audio files. Users can upload PDF documents and choose from various styles like sci-fi, fantasy, and public radio to generate personalized podcast scripts and audio experiences. With lifelike voiceovers, seamless integration, personalized templates, collaboration features, and easy navigation, Podbrews offers a cutting-edge solution for content consumption. The tool is designed to make consuming content enjoyable and efficient, providing users with a unique audio experience tailored to their preferences.

DocsAI is an AI-powered document companion that helps you organize, search, and chat with your documents. It integrates with various sources, including websites, text files, PDFs, Docx, Notion, and Confluence. You can customize the companion's appearance to match your brand and suggest better answers to improve its accuracy. DocsAI also offers a chat widget that can be embedded on any website, allowing you to chat with your documents and get summaries, insights, and leads. It is mobile and tablet-friendly, and you can export chats and analyze data to identify trends and improve customer satisfaction. DocsAI is open source and offers custom prompts and multi-language support.

Writeprint.ai is an AI tool designed to humanize AI-generated content. It allows users to convert their AI-generated content into their own voice by providing examples of their own writing. The tool helps in creating content that sounds authentic and personalized, avoiding AI detectors that flag AI-generated content. Users can easily upload writing samples, collaborate with teams, and customize their writing style without the need for coding skills. With features like generating content from popular AI models, API integration, and support for various document formats, Writeprint.ai simplifies the process of creating humanlike AI content.

Deflekt.ai is an AI-powered application designed to automate replies on all support channels. It helps businesses deflect customer and coworker support tickets by answering questions automatically. The tool can be integrated with various channels like web chat, email, Slack, and Teams, making it a versatile solution for support teams. Deflekt.ai allows users to customize content, localize responses, and provide human support when needed. With features like document hosting, channel activation, and conversation monitoring, Deflekt.ai streamlines support processes and reduces workload.

Boldicius is an AI tool designed to quickly create precise software proposals and project definitions. It simplifies the documentation of requirements, allowing users to present their proposals with confidence and elevate them to excellence. With features like saving time in project management, accurate and comprehensive document generation, customized review for quality, and interactivity for accuracy, Boldicius revolutionizes efficiency and quality in software projects. The tool has received positive feedback from industry leaders for its unmatched intelligence and ability to optimize planning time and elevate project quality.

AutoNotes is a leading healthcare AI Progress Note tool that offers AI-powered clinical documentation templates for generating SOAP Notes, DAP Notes, Treatment Plans, and more. It provides a user-friendly interface for therapists and healthcare professionals to create detailed and customizable clinical notes efficiently. With features like summarizing sessions, editing and downloading notes, and simple pricing plans, AutoNotes aims to streamline the documentation process in healthcare settings. The platform also offers advanced features like template customization, secure document storage, and dictation for voice-to-text conversion. Users can benefit from the platform's customization options, seamless integration with workflows, and responsive customer support.

AI Assistify is an AI-powered virtual assistant application designed to streamline workflows for daily life and business. It offers a centralized platform to access various AI models, allowing users to build custom AI agents without any coding requirements. The application enhances productivity by providing humanlike chat experiences, document summarization, prompt libraries, and access to tools like stocks, weather, and news. AI Assistify is fully customizable, integrates with popular social networks, and ensures privacy and security with locally stored API keys.

Strut is a complete writing workspace that combines notes, documents, and writing projects in collaborative workspaces supported by AI. It helps users capture notes, organize projects, and collaborate with their team alongside AI to keep the writing process moving forward. Strut offers deep focus modes, project workspaces organization, desktop app accessibility, writing inbox for capturing ideas, drag & drop document management, AI-powered chat for document/project discussions, AI workflows for brainstorming, voice & tone customization, inline editing, and typewriter-inspired focus mode.

FlowHunt is an AI chatbot platform that offers a new no-code visual way to build AI tools and chatbots for websites. It provides a template library with ready-to-use options, from simple AI tools to complex chatbots, and integrates with popular services like Smartsupp, LiveChat, HubSpot, and LiveAgent. The platform also features components like Task Decomposition, Query Expansion, Chat Input, Chat Output, Document Retriever, Document to Text, Generator, and GoogleSearch, enabling users to create customized chatbots for various contexts. FlowHunt aims to simplify the process of building and deploying AI-powered solutions for customer service and content generation.

v0 Report is an advanced AI Document Generator that enables users to effortlessly create, customize, and manage professional-quality documents. It utilizes cutting-edge natural language processing algorithms to automate the writing process, enhance workflow productivity, and elevate the quality of documents for students, researchers, and professionals.

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.

**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.

DB-GPT is a personal database administrator that can solve database problems by reading documents, using various tools, and writing analysis reports. It is currently undergoing an upgrade. **Features:** * **Online Demo:** * Import documents into the knowledge base * Utilize the knowledge base for well-founded Q&A and diagnosis analysis of abnormal alarms * Send feedbacks to refine the intermediate diagnosis results * Edit the diagnosis result * Browse all historical diagnosis results, used metrics, and detailed diagnosis processes * **Language Support:** * English (default) * Chinese (add "language: zh" in config.yaml) * **New Frontend:** * Knowledgebase + Chat Q&A + Diagnosis + Report Replay * **Extreme Speed Version for localized llms:** * 4-bit quantized LLM (reducing inference time by 1/3) * vllm for fast inference (qwen) * Tiny LLM * **Multi-path extraction of document knowledge:** * Vector database (ChromaDB) * RESTful Search Engine (Elasticsearch) * **Expert prompt generation using document knowledge** * **Upgrade the LLM-based diagnosis mechanism:** * Task Dispatching -> Concurrent Diagnosis -> Cross Review -> Report Generation * Synchronous Concurrency Mechanism during LLM inference * **Support monitoring and optimization tools in multiple levels:** * Monitoring metrics (Prometheus) * Flame graph in code level * Diagnosis knowledge retrieval (dbmind) * Logical query transformations (Calcite) * Index optimization algorithms (for PostgreSQL) * Physical operator hints (for PostgreSQL) * Backup and Point-in-time Recovery (Pigsty) * **Continuously updated papers and experimental reports** This project is constantly evolving with new features. Don't forget to star ⭐ and watch 👀 to stay up to date.

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.

Project Lakechain is a cloud-native, AI-powered framework for building document processing pipelines on AWS. It provides a composable API with built-in middlewares for common tasks, scalable architecture, cost efficiency, GPU and CPU support, and the ability to create custom transform middlewares. With ready-made examples and emphasis on modularity, Lakechain simplifies the deployment of scalable document pipelines for tasks like metadata extraction, NLP analysis, text summarization, translations, audio transcriptions, computer vision, and more.

BlinkID iOS is a mobile SDK that enables developers to easily integrate ID scanning and data extraction capabilities into their iOS applications. The SDK supports scanning and processing various types of identity documents, such as passports, driver's licenses, and ID cards. It provides accurate and fast data extraction, including personal information and document details. With BlinkID iOS, developers can enhance their apps with secure and reliable ID verification functionality, improving user experience and streamlining identity verification processes.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

doc2plan is a browser-based application that helps users create personalized learning plans by extracting content from documents. It features a Creator for manual or AI-assisted plan construction and a Viewer for interactive plan navigation. Users can extract chapters, key topics, generate quizzes, and track progress. The application includes AI-driven content extraction, quiz generation, progress tracking, plan import/export, assistant management, customizable settings, viewer chat with text-to-speech and speech-to-text support, and integration with various Retrieval-Augmented Generation (RAG) models. It aims to simplify the creation of comprehensive learning modules tailored to individual needs.

Crawl4AI is a powerful and free web crawling service that extracts valuable data from websites and provides LLM-friendly output formats. It supports crawling multiple URLs simultaneously, replaces media tags with ALT, and is completely free to use and open-source. Users can integrate Crawl4AI into Python projects as a library or run it as a standalone local server. The tool allows users to crawl and extract data from specified URLs using different providers and models, with options to include raw HTML content, force fresh crawls, and extract meaningful text blocks. Configuration settings can be adjusted in the `crawler/config.py` file to customize providers, API keys, chunk processing, and word thresholds. Contributions to Crawl4AI are welcome from the open-source community to enhance its value for AI enthusiasts and developers.

Sycamore is a conversational search and analytics platform for complex unstructured data, such as documents, presentations, transcripts, embedded tables, and internal knowledge repositories. It retrieves and synthesizes high-quality answers through bringing AI to data preparation, indexing, and retrieval. Sycamore makes it easy to prepare unstructured data for search and analytics, providing a toolkit for data cleaning, information extraction, enrichment, summarization, and generation of vector embeddings that encapsulate the semantics of data. Sycamore uses your choice of generative AI models to make these operations simple and effective, and it enables quick experimentation and iteration. Additionally, Sycamore uses OpenSearch for indexing, enabling hybrid (vector + keyword) search, retrieval-augmented generation (RAG) pipelining, filtering, analytical functions, conversational memory, and other features to improve information retrieval.

NeMo Curator is a GPU-accelerated open-source framework designed for efficient large language model data curation. It provides scalable dataset preparation for tasks like foundation model pretraining, domain-adaptive pretraining, supervised fine-tuning, and parameter-efficient fine-tuning. The library leverages GPUs with Dask and RAPIDS to accelerate data curation, offering customizable and modular interfaces for pipeline expansion and model convergence. Key features include data download, text extraction, quality filtering, deduplication, downstream-task decontamination, distributed data classification, and PII redaction. NeMo Curator is suitable for curating high-quality datasets for large language model training.

ERAG is an advanced system that combines lexical, semantic, text, and knowledge graph searches with conversation context to provide accurate and contextually relevant responses. This tool processes various document types, creates embeddings, builds knowledge graphs, and uses this information to answer user queries intelligently. It includes modules for interacting with web content, GitHub repositories, and performing exploratory data analysis using various language models.

Dify is an open-source LLM app development platform that combines AI workflow, RAG pipeline, agent capabilities, model management, observability features, and more. It allows users to quickly go from prototype to production. Key features include: 1. Workflow: Build and test powerful AI workflows on a visual canvas. 2. Comprehensive model support: Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions. 3. Prompt IDE: Intuitive interface for crafting prompts, comparing model performance, and adding additional features. 4. RAG Pipeline: Extensive RAG capabilities that cover everything from document ingestion to retrieval. 5. Agent capabilities: Define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools. 6. LLMOps: Monitor and analyze application logs and performance over time. 7. Backend-as-a-Service: All of Dify's offerings come with corresponding APIs for easy integration into your own business logic.

R2R (RAG to Riches) is a fast and efficient framework for serving high-quality Retrieval-Augmented Generation (RAG) to end users. The framework is designed with customizable pipelines and a feature-rich FastAPI implementation, enabling developers to quickly deploy and scale RAG-based applications. R2R was conceived to bridge the gap between local LLM experimentation and scalable production solutions. **R2R is to LangChain/LlamaIndex what NextJS is to React**. A JavaScript client for R2R deployments can be found here. ### Key Features * **🚀 Deploy** : Instantly launch production-ready RAG pipelines with streaming capabilities. * **🧩 Customize** : Tailor your pipeline with intuitive configuration files. * **🔌 Extend** : Enhance your pipeline with custom code integrations. * **⚖️ Autoscale** : Scale your pipeline effortlessly in the cloud using SciPhi. * **🤖 OSS** : Benefit from a framework developed by the open-source community, designed to simplify RAG deployment.

Firecrawl is an API service that takes a URL, crawls it, and converts it into clean markdown. It crawls all accessible subpages and provides clean markdown for each, without requiring a sitemap. The API is easy to use and can be self-hosted. It also integrates with Langchain and Llama Index. The Python SDK makes it easy to crawl and scrape websites in Python code.

This repository contains sample code demonstrating various use cases leveraging Amazon Bedrock and Generative AI. Each sample is a separate project with its own directory, and includes a basic Streamlit frontend to help users quickly set up a proof of concept.

SWIFT (Scalable lightWeight Infrastructure for Fine-Tuning) supports training, inference, evaluation and deployment of nearly **200 LLMs and MLLMs** (multimodal large models). Developers can directly apply our framework to their own research and production environments to realize the complete workflow from model training and evaluation to application. In addition to supporting the lightweight training solutions provided by [PEFT](https://github.com/huggingface/peft), we also provide a complete **Adapters library** to support the latest training techniques such as NEFTune, LoRA+, LLaMA-PRO, etc. This adapter library can be used directly in your own custom workflow without our training scripts. To facilitate use by users unfamiliar with deep learning, we provide a Gradio web-ui for controlling training and inference, as well as accompanying deep learning courses and best practices for beginners. Additionally, we are expanding capabilities for other modalities. Currently, we support full-parameter training and LoRA training for AnimateDiff.

EasyInstruct is a Python package proposed as an easy-to-use instruction processing framework for Large Language Models (LLMs) like GPT-4, LLaMA, ChatGLM in your research experiments. EasyInstruct modularizes instruction generation, selection, and prompting, while also considering their combination and interaction.

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Contracter.ai is a specialized GPT designed to assist users in generating customized legal contracts

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