Best AI tools for< Redact Pdf Data >

Docalysis is an AI-powered tool that allows you to chat with your PDF files. It can answer your questions about your files within seconds, saving you hours of time. Docalysis is secure and easy to use. Simply upload your PDF file and start chatting with the AI.

The AI PDF redaction tool App is a powerful application designed to assist users in redacting sensitive information from PDF documents with ease and efficiency. By leveraging artificial intelligence technology, this tool automates the process of identifying and removing confidential data, ensuring data privacy and security. With a user-friendly interface, users can quickly upload PDF files, select the information to redact, and generate secure, sanitized documents for sharing or storage. The tool is ideal for individuals and organizations that handle sensitive information and require a reliable solution for data redaction.

HiPDF is a free online PDF solution that offers a wide range of tools for editing, converting, compressing, and organizing PDFs. It also includes AI-powered tools such as Chat with PDF and AI Detector. With HiPDF, you can easily edit PDFs in your browser, convert PDFs to and from other formats, compress PDFs to reduce their size, and merge, split, and extract images from PDFs. You can also protect your PDFs with passwords and redact sensitive information. HiPDF is a convenient and easy-to-use tool that can help you with all your PDF needs.

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.

Super.AI provides Intelligent Document Processing (IDP) solutions powered by Large Language Models (LLMs) and human-in-the-loop (HITL) capabilities. It automates document processing tasks such as data extraction, classification, and redaction, enabling businesses to streamline their workflows and improve accuracy. Super.AI's platform leverages cutting-edge AI models from providers like Amazon, Google, and OpenAI to handle complex documents, ensuring high-quality outputs. With its focus on accuracy, flexibility, and scalability, Super.AI caters to various industries, including financial services, insurance, logistics, and healthcare.

Sighthound is an AI-powered video solutions provider that specializes in solving complex video AI problems at scale. Their products, such as Sighthound ALPR+ for Automatic License Plate Recognition and Sighthound Redactor for Video Redaction, leverage deep learning technology to unlock valuable user insights, reduce operational costs, and increase revenue in the privacy and vehicle recognition space. With a focus on simplicity and customer support, Sighthound offers easy integration of their AI products through simple-to-use APIs.

Base64.ai is an automated document processing API that offers a leading no-code AI solution for understanding documents, photos, and videos. It provides a comprehensive set of features for document processing across various industries, with a strong focus on accuracy, security, and extensibility. Base64.ai is designed to streamline document automation processes and improve data extraction efficiency.

ResuMetrics is an AI-powered platform designed to streamline the resume processing workflow. It offers solutions to extract structured data from resumes and automate the anonymization process. The platform provides an easy-to-use API for automating resume analysis, including candidate onboarding and PII redaction. With features like resume scoring and vacancy matching on the roadmap, ResuMetrics aims to enhance the efficiency of resume processing tasks. Users can choose from different subscription plans based on their processing needs, with credits consumed per document page. Overall, ResuMetrics is a comprehensive tool for organizations looking to optimize their resume processing operations.

Refact.ai is an open-source AI coding assistant that offers a range of features including code completion, refactoring, and chat. It supports various LLMs such as GPT-4 and Code LLama, allowing users to choose the model that best suits their needs. Refact understands the context of the codebase using a fill-in-the-middle technique, providing relevant suggestions. Users can opt for a self-hosted version or adjust privacy settings for the plugin.

React Native Starter AI is an all-in-one development kit designed to help users quickly launch their mobile apps with AI functionality. The boilerplate template includes integrations such as AI tools, Firebase functions, analytics, authentication, in-app purchases, and more. It aims to save developers time by providing pre-built components and screens for building AI mobile applications. With React Native Starter AI, users can easily customize and publish their apps on mobile app stores, catering to both beginner and experienced developers.

Quest is a web-based application that allows users to generate React code from their designs. It incorporates AI models to generate real, useful code that incorporates all the things professional developers care about. Users can use Quest to build new applications, add to existing applications, and create design systems and libraries. Quest is made for development teams and integrates with the design and dev tools that users love. It is also built for the most demanding product teams and can be used to build new applications, build web pages, and create component templates.

GitWit is an online tool that helps you build web apps quickly and easily, even if you don't have any coding experience. With GitWit, you can create a React app in minutes, and you can use AI to augment your own coding skills. GitWit supports React, Tailwind, and NodeJS, and it has generated over 1000 projects to date. GitWit can help you build any type of web app, from simple landing pages to complex e-commerce stores.

Glass is an AI copilot designed for React and Next.js developers. It allows users to edit code straight from the browser using AI technology. Glass's AI capabilities include creating components, modifying props, and generating Tailwind CSS. The tool helps developers visualize component structures and easily navigate to source code. Glass is precise and efficient, making React coding faster and more streamlined. It is currently in open beta for startups, with ongoing improvements to its AI functionality.

Replexica is an AI-powered i18n compiler for React that is JSON-free and LLM-backed. It is designed for shipping multi-language frontends fast.

Belva is an AI-powered phone-calling assistant that can make calls on your behalf. With Belva, you can simply state your objective and the AI will make the call for you, providing you with a live transcription of the conversation. Belva's envoys can handle a variety of tasks, from making appointments and reservations to solving customer issues. You can monitor your active calls in real-time or review saved transcripts to collect information from the call. With Belva, you can get off the phone and let the AI do the talking, saving you time and hassle.

Watto AI is a platform that offers Conversational AI solutions to businesses, allowing them to build AI voice agents without the need for coding. The platform enables users to collect leads, automate customer support, and facilitate natural interactions through AI voice bots. Watto AI caters to various industries and scenarios, providing human-like conversational AI for mystery shopping, top-quality customer support, and restaurant assistance.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::n894q-1726678978147-1c9e4ad82a70) for reference. Users are directed to check the documentation for further information and troubleshooting.

Infinite Meals is a web application that provides users with a new meal idea every day. It is powered by GPT-3.5-Turbo-1106 from Open AI. The application is designed to help users find new and exciting recipes to cook. It offers a variety of features, including the ability to search for recipes by category, ingredient, or cuisine. Users can also save their favorite recipes and create meal plans.

Voice AI Note is a web-based application that allows users to quickly and easily create voice notes using advanced AI. With Voice AI Note, you can create voice notes that are fluent, accurate, and sound natural. The application is easy to use and requires no prior experience with AI or voice recording. Simply enter the text you want to convert to speech, and Voice AI Note will do the rest.

TAID is a cutting-edge AI tool that specializes in analyzing text to determine whether it was created by a human or generated by artificial intelligence models like ChatGPT. It helps users combat misinformation, ensure transparency, and maintain trust in online communication by verifying the authenticity of the text they encounter. TAID utilizes advanced machine learning algorithms to achieve impressive accuracy in detecting AI-generated content, offering a free detection service with unlimited usage and no hidden fees or subscriptions.

DL3DV-10K is a large-scale dataset of real-world scene-level videos with annotations, covering diverse scenes with different levels of reflection, transparency, and lighting. It includes 10,510 multi-view scenes with 51.2 million frames at 4k resolution, and offers benchmark videos for novel view synthesis (NVS) methods. The dataset is designed to facilitate research in deep learning-based 3D vision and provides valuable insights for future research in NVS and 3D representation learning.

This solution provides a low-code ReactJS application to prototype and vet business use cases for GenAI using Retrieval Augmented Generation (RAG). It includes a backend Flask application that uses LangChain to provide PDF data as embeddings to a text-gen model via Amazon Bedrock and a vector database with FAISS or Kendra Index. The solution utilizes Amazon Bedrock as the only cost-generating AWS service.

The serverless-pdf-chat repository contains a sample application that allows users to ask natural language questions of any PDF document they upload. It leverages serverless services like Amazon Bedrock, AWS Lambda, and Amazon DynamoDB to provide text generation and analysis capabilities. The application architecture involves uploading a PDF document to an S3 bucket, extracting metadata, converting text to vectors, and using a LangChain to search for information related to user prompts. The application is not intended for production use and serves as a demonstration and educational tool.

Uxie is a PDF reader app designed to revolutionize the learning experience. It offers features such as annotation, note-taking, collaboration tools, integration with LLM for enhanced learning, and flashcard generation with LLM feedback. Built using Nextjs, tRPC, Zod, TypeScript, Tailwind CSS, React Query, React Hook Form, Supabase, Prisma, and various other tools. Users can take notes, summarize PDFs, chat and collaborate with others, create custom blocks in the editor, and use AI-powered text autocompletion. The tool allows users to craft simple flashcards, test knowledge, answer questions, and receive instant feedback through AI evaluation.

LLM-PLSE-paper is a repository focused on the applications of Large Language Models (LLMs) in Programming Language and Software Engineering (PL/SE) domains. It covers a wide range of topics including bug detection, specification inference and verification, code generation, fuzzing and testing, code model and reasoning, code understanding, IDE technologies, prompting for reasoning tasks, and agent/tool usage and planning. The repository provides a comprehensive collection of research papers, benchmarks, empirical studies, and frameworks related to the capabilities of LLMs in various PL/SE tasks.

EdgeChains is an open-source chain-of-thought engineering framework tailored for Large Language Models (LLMs)- like OpenAI GPT, LLama2, Falcon, etc. - With a focus on enterprise-grade deployability and scalability. EdgeChains is specifically designed to **orchestrate** such applications. At EdgeChains, we take a unique approach to Generative AI - we think Generative AI is a deployment and configuration management challenge rather than a UI and library design pattern challenge. We build on top of a tech that has solved this problem in a different domain - Kubernetes Config Management - and bring that to Generative AI. Edgechains is built on top of jsonnet, originally built by Google based on their experience managing a vast amount of configuration code in the Borg infrastructure.

This repository provides a systematic and comprehensive review of efficient LLMs research. We organize the literature in a taxonomy consisting of three main categories, covering distinct yet interconnected efficient LLMs topics from **model-centric** , **data-centric** , and **framework-centric** perspective, respectively. We hope our survey and this GitHub repository can serve as valuable resources to help researchers and practitioners gain a systematic understanding of the research developments in efficient LLMs and inspire them to contribute to this important and exciting field.

This repository contains a curated list of resources on generative information retrieval, including research papers, datasets, tools, and applications. Generative information retrieval is a subfield of information retrieval that uses generative models to generate new documents or passages of text that are relevant to a given query. This can be useful for a variety of tasks, such as question answering, summarization, and document generation. The resources in this repository are intended to help researchers and practitioners stay up-to-date on the latest advances in generative information retrieval.

This repository serves as a practical guide for Medical Large Language Models (Medical LLMs) and provides resources, surveys, and tools for building, fine-tuning, and utilizing LLMs in the medical domain. It covers a wide range of topics including pre-training, fine-tuning, downstream biomedical tasks, clinical applications, challenges, future directions, and more. The repository aims to provide insights into the opportunities and challenges of LLMs in medicine and serve as a practical resource for constructing effective medical LLMs.

Dynamiq is an orchestration framework designed to streamline the development of AI-powered applications, specializing in orchestrating retrieval-augmented generation (RAG) and large language model (LLM) agents. It provides an all-in-one Gen AI framework for agentic AI and LLM applications, offering tools for multi-agent orchestration, document indexing, and retrieval flows. With Dynamiq, users can easily build and deploy AI solutions for various tasks.

The Google Cloud Document AI Samples repository contains code samples and Community Samples demonstrating how to analyze, classify, and search documents using Google Cloud Document AI. It includes various projects showcasing different functionalities such as integrating with Google Drive, processing documents using Python, content moderation with Dialogflow CX, fraud detection, language extraction, paper summarization, tax processing pipeline, and more. The repository also provides access to test document files stored in a publicly-accessible Google Cloud Storage Bucket. Additionally, there are codelabs available for optical character recognition (OCR), form parsing, specialized processors, and managing Document AI processors. Community samples, like the PDF Annotator Sample, are also included. Contributions are welcome, and users can seek help or report issues through the repository's issues page. Please note that this repository is not an officially supported Google product and is intended for demonstrative purposes only.

This repository focuses on exploring tools that enhance the performance of language models for various tasks. It provides a structured list of literature relevant to tool-augmented language models, covering topics such as tool basics, tool use paradigm, scenarios, advanced methods, and evaluation. The repository includes papers, preprints, and books that discuss the use of tools in conjunction with language models for tasks like reasoning, question answering, mathematical calculations, accessing knowledge, interacting with the world, and handling non-textual modalities.

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.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

I extract data and tables from PDFs to CSV, focusing on data privacy and precision.

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