Best AI tools for< Information Extraction Specialist >

Isomeric is an AI tool that uses artificial intelligence to semantically understand unstructured text and extract specific data. It helps transform messy text into machine-readable JSON, enabling tasks such as web scraping, browser extensions, and general information extraction. With Isomeric, users can easily gather insights, process data, deliver results, and more, making data gathering and analysis efficient and scalable.

NuShift Inc is an AI-powered application that offers ELMR-T, a cutting-edge solution for converting data into actionable knowledge in the maintenance and engineering domain. Leveraging machine learning, machine translation, speech recognition, question answering, and information extraction, ELMR-T provides intelligent AI insights to empower maintenance teams. The application is designed to streamline data-driven decision-making, enhance user interaction, and boost efficiency by delivering precise and meaningful results effortlessly.

Daxtra is an AI-powered recruitment technology tool designed to help staffing and recruiting professionals find, parse, match, and engage the best candidates quickly and efficiently. The tool offers a suite of products that seamlessly integrate with existing ATS or CRM systems, automating various recruitment processes such as candidate data loading, CV/resume formatting, information extraction, and job matching. Daxtra's solutions cater to corporates, vendors, job boards, and social media partners, providing a comprehensive set of developer components to enhance recruitment workflows.

deepset is an AI platform that offers enterprise-level products and solutions for AI teams. It provides deepset Cloud, a platform built with Haystack, enabling fast and accurate prototyping, building, and launching of advanced AI applications. The platform streamlines the AI application development lifecycle, offering processes, tools, and expertise to move from prototype to production efficiently. With deepset Cloud, users can optimize solution accuracy, performance, and cost, and deploy AI applications at any scale with one click. The platform also allows users to explore new models and configurations without limits, extending their team with access to world-class AI engineers for guidance and support.

Inkwise is an AI-powered platform that helps users craft expert documents by extracting and integrating key information seamlessly from uploaded files. The platform offers features such as smart content extraction, predictive writing, document templates, and AI chat with files. Inkwise automates the document creation process by analyzing uploaded documents, extracting relevant data, and integrating it into customizable templates. It caters to various professions including academics, accounting, finance, corporate treasury, corporate tax, product management, procurement, legal, and marketing.

PYQ is an AI-powered platform that helps businesses automate document-related tasks, such as data extraction, form filling, and system integration. It uses natural language processing (NLP) and machine learning (ML) to understand the content of documents and perform tasks accordingly. PYQ's platform is designed to be easy to use, with pre-built automations for common use cases. It also offers custom automation development services for more complex needs.

Docugami is an AI-powered document engineering platform that enables business users to extract, analyze, and automate data from various types of documents. It empowers users with immediate impact without the need for extensive machine learning investments or IT development. Docugami's proprietary Business Document Foundation Model leverages Generative AI to transform unstructured text into structured information, allowing users to unlock insights and drive business processes efficiently.

TextMine is an AI-powered knowledge base that helps businesses analyze, manage, and search thousands of documents. It uses AI to analyze unstructured textual data and document databases, automatically retrieving key terms to help users make informed decisions. TextMine's features include a document vault for storing and managing documents, a categorization system for organizing documents, and a data extraction tool for extracting insights from documents. TextMine can help businesses save time, money, and improve efficiency by automating manual data entry and information retrieval tasks.

Pentest Copilot by BugBase is an ultimate ethical hacking assistant that guides users through each step of the hacking journey, from analyzing web apps to root shells. It eliminates redundant research, automates payload and command generation, and provides intelligent contextual analysis to save time. The application excels at data extraction, privilege escalation, lateral movement, and leaving no trace behind. With features like secure VPN integration, total control over sessions, parallel command processing, and flexibility to choose between local or cloud execution, Pentest Copilot offers a seamless and efficient hacking experience without the need for Kali Linux installation.

Ragie is a fully managed RAG-as-a-Service platform designed for developers. It offers easy-to-use APIs and SDKs to help developers get started quickly, with advanced features like LLM re-ranking, summary index, entity extraction, flexible filtering, and hybrid semantic and keyword search. Ragie allows users to connect directly to popular data sources like Google Drive, Notion, Confluence, and more, ensuring accurate and reliable information delivery. The platform is led by Craft Ventures and offers seamless data connectivity through connectors. Ragie simplifies the process of data ingestion, chunking, indexing, and retrieval, making it a valuable tool for AI applications.

FB Group Extractor is an AI-powered tool designed to scrape Facebook group members' data with one click. It allows users to easily extract, analyze, and utilize valuable information from Facebook groups using artificial intelligence technology. The tool provides features such as data extraction, behavioral analytics for personalized ads, content enhancement, user research, and more. With over 10k satisfied users, FB Group Extractor offers a seamless experience for businesses to enhance their marketing strategies and customer insights.

Automaited is an AI application that offers Ada - an AI Agent for automating order processing. Ada handles orders from receipt to ERP entry, extracting, validating, and transferring data to ensure accuracy and efficiency. The application utilizes state-of-the-art AI technology to streamline order processing, saving time, reducing errors, and enabling users to focus on customer satisfaction. With seamless automation, Ada integrates into ERP systems, making order processing effortless, quick, and cost-efficient. Automaited provides tailored automations to make operational processes up to 70% more efficient, enhancing performance and reducing error rates.

SkipWatch is an AI-powered YouTube summarizer that allows users to quickly generate video summaries, saving time and enhancing learning efficiency. With SkipWatch, users can access key information from YouTube videos in seconds, breaking language barriers and accelerating learning. The tool is designed to boost productivity by providing instant video summaries and extracting essential content from videos. Users can easily install SkipWatch as a Chrome extension and enjoy the benefits of efficient content consumption.

Woy AI Tools is an online tool that offers free image to text conversion with over 99% accuracy and automatic recognition of more than 100 languages. Users can easily upload an image and receive the textual information contained within it. The tool supports multiple languages, prioritizes user privacy and data protection, has a simple and user-friendly interface, and is available for free usage. It utilizes advanced machine learning and OCR technology to continuously optimize recognition algorithms for clear and high-resolution images.

Schemawriter.ai is an advanced AI software platform that generates optimized schema and content on autopilot. It uses a large number of external APIs, including several Google APIs, and complex mathematical algorithms to produce entity lists and content correlated with high rankings in Google. The platform connects directly to Wikipedia and Wikidata via APIs to deliver accurate information about content and entities on webpages. Schemawriter.ai simplifies the process of editing schema, generating advanced schema files, and optimizing webpage content for fast and permanent on-page SEO optimization.

Dost is an AI-powered platform that automates the management of invoices and delivery notes. It offers solutions for creating, customizing, and managing supplier portals, capturing and collecting documents automatically, extracting necessary information, automating reconciliation of invoices, delivery notes, and orders, creating and modifying automatic approval workflows, and integrating data sources and ERPs. The platform also provides resources such as a blog, webinars, newsletters, success stories, and ebooks. Dost aims to streamline financial department processes by digitizing invoices and delivery notes, reducing administrative costs, eliminating human errors, and providing visibility and control through a single platform.

InstantAPI.ai is an AI-powered web scraping tool that allows developers, data scientists, and SEO specialists to instantly turn any web page into a personalized API. With the ability to effortlessly scrape, customize, and integrate data, users can enhance their projects, drive insights, and optimize performance. The tool offers features such as scraping precise data, transforming information into various formats, generating new content, providing advanced analysis, and extracting valuable insights from data. Users can tailor the output to meet specific needs and unleash creativity by using AI for unique purposes. InstantAPI.ai simplifies the process of web scraping and data manipulation, offering a seamless experience for users seeking to leverage AI technology for their projects.

HireMatch is an AI-powered resume screening tool designed for recruiters. It automates the process of screening and analyzing resumes to identify top candidates for job positions. By leveraging Neural Language Processing algorithms, HireMatch saves time by extracting and interpreting relevant information from resumes. The tool caters to various industries and positions, offering a data-rich dashboard for easy comparison of skills and experience. Whether you are an HR manager in a small team or a freelance recruiter handling numerous resumes, HireMatch streamlines the candidate selection process and enhances recruitment efficiency.

The FileAI website offers an AI-powered file reading assistant that specializes in data extraction from structured documents like financial statements, legal documents, and research papers. It automates tasks related to legal and compliance review, finance and accounting report preparation, and research and academia support. The tool aims to streamline document processing, enhance learning processes, and improve research efficiency. With features like summarizing complex texts, extracting key information, and detecting plagiarism, FileAI caters to users in various industries and educational fields. The platform prioritizes data security and user privacy, ensuring that data is used solely for its intended purpose and deleted after 7 days of non-use.

SOMA is a Research Automation Platform that accelerates medical innovation by providing up to 100x speedup through process automation. The platform collates and analyzes medical research articles, extracting important concepts and identifying causal and associative relationships between them. It organizes this information into a specialized database forming a knowledge graph. Researchers can retrieve causal chains, access specific research articles, and build pipelines for tasks like article search, concept analysis, drug repurposing, and target discovery. SOMA enhances literature review by finding relevant articles based on causal chains and keywords, enabling users to uncover hidden connections efficiently. The platform is freemium, offering basic functionality for free with the option to subscribe for advanced features.

AnyLabeling is a tool for effortless data labeling with AI support from YOLO and Segment Anything. It combines features from LabelImg and Labelme with an improved UI and auto-labeling capabilities. Users can annotate images with polygons, rectangles, circles, lines, and points, as well as perform auto-labeling using YOLOv5 and Segment Anything. The tool also supports text detection, recognition, and Key Information Extraction (KIE) labeling, with multiple language options available such as English, Vietnamese, and Chinese.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

Awesome MLSecOps is a curated list of open-source tools, resources, and tutorials for MLSecOps (Machine Learning Security Operations). It includes a wide range of security tools and libraries for protecting machine learning models against adversarial attacks, as well as resources for AI security, data anonymization, model security, and more. The repository aims to provide a comprehensive collection of tools and information to help users secure their machine learning systems and infrastructure.

This repository, Awesome-LLM-Survey, serves as a comprehensive collection of surveys related to Large Language Models (LLM). It covers various aspects of LLM, including instruction tuning, human alignment, LLM agents, hallucination, multi-modal capabilities, and more. Researchers are encouraged to contribute by updating information on their papers to benefit the LLM survey community.

KAG is a logical reasoning and Q&A framework based on the OpenSPG engine and large language models. It is used to build logical reasoning and Q&A solutions for vertical domain knowledge bases. KAG supports logical reasoning, multi-hop fact Q&A, and integrates knowledge and chunk mutual indexing structure, conceptual semantic reasoning, schema-constrained knowledge construction, and logical form-guided hybrid reasoning and retrieval. The framework includes kg-builder for knowledge representation and kg-solver for logical symbol-guided hybrid solving and reasoning engine. KAG aims to enhance LLM service framework in professional domains by integrating logical and factual characteristics of KGs.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

This repository is dedicated to collecting and categorizing papers related to Retrieval-Augmented Generation (RAG) for AI-generated content. It serves as a survey repository based on the paper 'Retrieval-Augmented Generation for AI-Generated Content: A Survey'. The repository is continuously updated to keep up with the rapid growth in the field of RAG.

ABigSurveyOfLLMs is a repository that compiles surveys on Large Language Models (LLMs) to provide a comprehensive overview of the field. It includes surveys on various aspects of LLMs such as transformers, alignment, prompt learning, data management, evaluation, societal issues, safety, misinformation, attributes of LLMs, efficient LLMs, learning methods for LLMs, multimodal LLMs, knowledge-based LLMs, extension of LLMs, LLMs applications, and more. The repository aims to help individuals quickly understand the advancements and challenges in the field of LLMs through a collection of recent surveys and research papers.

LangChain.dart is a Dart port of the popular LangChain Python framework created by Harrison Chase. LangChain provides a set of ready-to-use components for working with language models and a standard interface for chaining them together to formulate more advanced use cases (e.g. chatbots, Q&A with RAG, agents, summarization, extraction, etc.). The components can be grouped into a few core modules: * **Model I/O:** LangChain offers a unified API for interacting with various LLM providers (e.g. OpenAI, Google, Mistral, Ollama, etc.), allowing developers to switch between them with ease. Additionally, it provides tools for managing model inputs (prompt templates and example selectors) and parsing the resulting model outputs (output parsers). * **Retrieval:** assists in loading user data (via document loaders), transforming it (with text splitters), extracting its meaning (using embedding models), storing (in vector stores) and retrieving it (through retrievers) so that it can be used to ground the model's responses (i.e. Retrieval-Augmented Generation or RAG). * **Agents:** "bots" that leverage LLMs to make informed decisions about which available tools (such as web search, calculators, database lookup, etc.) to use to accomplish the designated task. The different components can be composed together using the LangChain Expression Language (LCEL).

AutoGroq is a revolutionary tool that dynamically generates tailored teams of AI agents based on project requirements, eliminating manual configuration. It enables users to effortlessly tackle questions, problems, and projects by creating expert agents, workflows, and skillsets with ease and efficiency. With features like natural conversation flow, code snippet extraction, and support for multiple language models, AutoGroq offers a seamless and intuitive AI assistant experience for developers and users.

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.

ScrapeGraphAI is a web scraping Python library that utilizes LangChain, LLM, and direct graph logic to create scraping pipelines. Users can specify the information they want to extract, and the library will handle the extraction process. This repository contains an official demo/trial for the ScrapeGraphAI library, showcasing its capabilities in web scraping tasks. The tool is designed to simplify the process of extracting data from websites by providing a user-friendly interface and powerful scraping functionalities.

SambaNova AI Starter Kits is a collection of open-source examples and guides designed to facilitate the deployment of AI-driven use cases for developers and enterprises. The kits cover various categories such as Data Ingestion & Preparation, Model Development & Optimization, Intelligent Information Retrieval, and Advanced AI Capabilities. Users can obtain a free API key using SambaNova Cloud or deploy models using SambaStudio. Most examples are written in Python but can be applied to any programming language. The kits provide resources for tasks like text extraction, fine-tuning embeddings, prompt engineering, question-answering, image search, post-call analysis, and more.

DOM to Semantic Markdown is a tool that converts HTML DOM to Semantic Markdown for use in Large Language Models (LLMs). It maximizes semantic information, token efficiency, and preserves metadata to enhance LLMs' processing capabilities. The tool captures rich web content structure, including semantic tags, image metadata, table structures, and link destinations. It offers customizable conversion options and supports both browser and Node.js environments.

**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.

The repository 'LLM-for-Healthcare' provides a comprehensive survey of large language models (LLMs) for healthcare, covering data, technology, applications, and accountability and ethics. It includes information on various LLM models, training data, evaluation methods, and computation costs. The repository also discusses tasks such as NER, text classification, question answering, dialogue systems, and generation of medical reports from images in the healthcare domain.

Clickolas-cage is a Chrome extension designed to autonomously perform web browsing actions to achieve specific goals using LLM as a brain. Users can interact with the extension by setting goals, which triggers a series of actions including navigation, element extraction, and step generation. The extension is developed using Node.js and can be locally run for testing and development purposes before packing it for submission to the Chrome Web Store.

Open Domain Relation Extractor

Expert in website summarization, providing clear and concise info summaries. You can also ask it to find specific info from the site.

What is Alien lyrics meaning? Alien singer：P. Sears, J. Sears，album：Modern Times ，album_time：1981. Click The LINK For More ↓↓↓

Converts graph triples to clear text, no assumptions.

上传一本书（PDF、Word、Txt），我来帮你提炼精华

1) Input a URL, attachment, or copy/paste a bunch of info about your biz. 2) I will return a summary of what's important. 3) Use what I give you for other prompts, e.g.: marketing strategy, content ideas, competitive analysis, etc

マルチモーダルデータからの情報抽出と解析を専門とする

Simply take a photo of your business cards and upload it to the chat. I'll take it from there!

请输入文章或者上载文件，专门于文档分析的阅读助手，会使用中文回复。

Extracts and formats procedures from manuals into templates

Expert in data extraction and context-driven analysis. Can read most filetypes including PDFS, XLSX, Word, TXT, CSV, EML, Etc.

Extracts and structures web content in formal, technical language.

Provide the information about each receipt from your shopping.

A digital librarian who identifies books from photos and provides detailed information.

我会将复杂的文本信息提炼成流程化的表达，辅助你快速了解一个流程。

📝 Multifaceted Document Transformation Expert

汇总PDF文档及其中的表格的专家

An Ivy Leage Scholar GPT equipped to understand your research needs, formulate comprehensive literature review strategies, and extract pertinent information from a plethora of academic databases and journals. I'll then compose a peer review-quality paper with citations.

A SID framework companion for understanding and utilizing the Information Framework.

Information on male menopause, providing insights and explanations.