Best AI tools for< Check Application >

Slick Write is a powerful, free AI application designed to help users check their writing for grammar errors, potential stylistic mistakes, and other features of interest. It goes beyond simple spell checking to teach users effective writing habits. Whether you're a blogger, novelist, SEO professional, or student, Slick Write can assist in improving your content's impact, readability, and overall quality.

Bibit AI is a real estate marketing AI designed to enhance the efficiency and effectiveness of real estate marketing and sales. It can help create listings, descriptions, and property content, and offers a host of other features. Bibit AI is the world's first AI for Real Estate. We are transforming the real estate industry by boosting efficiency and simplifying tasks like listing creation and content generation.

HireFlow.net is an AI-powered platform designed to optimize resumes and enhance job prospects. The website offers a free resume checker that leverages advanced Artificial Intelligence technology to provide personalized feedback and suggestions for improving resumes. Users can also access features such as CV analysis, cover letter and resignation letter generators, and expert insights to stand out in the competitive job market.

AI Powered Resume Checker is an AI-driven resume review tool that helps job seekers create impactful resumes that stand out in the job market. With detailed analysis, tailored suggestions, keyword optimization, and formatting tips, the tool empowers users to elevate their resumes and increase their chances of getting noticed by potential employers. The resume review is crafted with insights from industry experts, career coaches, and hiring managers, providing valuable guidance to job seekers.

Resumecheck.net is an AI-powered resume improvement platform that helps users create error-free, professional resumes that stand out to recruiters. The platform uses GPT4 technology to provide personalized feedback and suggestions, including grammar corrections, formatting adjustments, and industry-specific keyword optimization. Additionally, Resumecheck.net offers an AI Cover Letter Writer that generates tailored cover letters based on the user's resume and the specific job position they are applying for.

Ferret is an AI-powered relationship intelligence tool designed to provide curated relationship intelligence and monitoring to help users avoid high-risk individuals and identify promising opportunities. It uses AI and proprietary data to deliver actionable intelligence in real-time, ensuring total transparency into personal and professional networks. The tool offers features such as Single Click Reputation & Safety Pre-Checks, Business and Personal Relationship Intelligence, AI Checks for Risks and Opportunities, and more. Ferret is a cutting-edge application that combines Artificial Intelligence with world-class information to provide users with comprehensive relationship intelligence.

Felix is a Slack AI assistant that helps you get work done faster and more efficiently. With Felix, you can: * Schedule meetings * Set reminders * Create tasks * Get news and weather updates * And much more!

Smodin is a multi-lingual writing assistance tool that provides a range of features to help users with their research and content creation needs. It offers AI-powered research tools, automatic reference generation, plagiarism detection, and instant feedback on writing. Smodin also includes a chat feature that allows users to ask questions and get answers on any subject. The tool is designed to help users write high-quality, structured text quickly and easily.

The AI Seed Phrase Finder & BTC balance checker tool for Windows PC is an innovative application designed to prevent the loss of access to Bitcoin wallets. Leveraging advanced algorithms and artificial intelligence techniques, this program efficiently analyzes vast amounts of data to pre-train AI models. Consequently, it generates and searches for mnemonic phrases that grant access to abandoned Bitcoin wallets holding nonzero balances. With the “AI Seed Finder tool for Windows PC”, locating a complete 12-word seed phrase for a specific Bitcoin wallet becomes effortless. Even if you possess only partial knowledge of the mnemonic phrase or individual words comprising it, this tool can swiftly identify the entire seed phrase. Furthermore, by providing the address of a specific Bitcoin wallet you wish to regain access to, the program narrows down the search area. This targeted approach significantly enhances the program’s efficiency and reduces the time required to ascertain the correct mnemonic phrase.

HowsThisGoing is an AI-powered application designed to streamline team communication and productivity by enabling users to set up standups in Slack within seconds. The platform offers features such as automatic standups, AI summaries, custom tests, analytics & reporting, and workflow scheduling. Users can easily create workflows, generate AI reports, and track team performance efficiently. HowsThisGoing provides unlimited benefits at a flat price, making it a cost-effective solution for teams of all sizes.

KZHU.ai is an online learning platform that offers a variety of courses in artificial intelligence, machine learning, data science, and other related fields. The platform is designed for both beginners and experienced professionals who want to learn more about AI and its applications.

Alice is a desktop application that provides access to advanced AI models like GPT-4, Perplexity, Claude 3, and others. It offers a user-friendly interface with features such as keyboard shortcuts, pre-built prompts (Snippets), and the ability to run automations within other applications. Alice is designed to enhance productivity and streamline tasks by providing quick access to AI-powered assistance.

This application utilizes AI technology to simplify the complex process of understanding health insurance policies. Unlike other apps that focus on insurance search and comparison, this app specializes in deciphering the intricate language found in policies. It provides instant access to policy analysis with a one-time payment, empowering users to gain clarity and make informed decisions regarding their health insurance coverage.

Teal is a career development platform that provides tools and resources to help users with their job search. The platform includes an AI resume builder, job application tracker, resume checker, cover letter generator, resume summary generator, and more. Teal also offers career advice and resources, such as a blog, resume examples, and cover letter examples.

MacWhisper is a native macOS application that utilizes OpenAI's Whisper technology for transcribing audio files into text. It offers a user-friendly interface for recording, transcribing, and editing audio, making it suitable for various use cases such as transcribing meetings, lectures, interviews, and podcasts. The application is designed to protect user privacy by performing all transcriptions locally on the device, ensuring that no data leaves the user's machine.

OpenFuture is the world's largest AI Tools Directory in 2024, offering a comprehensive collection of AI applications across various categories such as 3D generator, aggregators, AI detection, art generator, audio editing, and more. Users can explore a wide range of AI-powered tools to enhance productivity, streamline tasks, and improve efficiency in different domains. The platform serves as a valuable resource for individuals and businesses looking to leverage artificial intelligence technology for various purposes.

The website is a platform that seems to be encountering an error related to client-side exceptions. The error message indicates that there is an issue with the application, prompting users to check the browser console for more details. It appears to be a technical problem that needs troubleshooting to resolve.

Diffblue Cover is an autonomous AI-powered unit test writing tool for Java development teams. It uses next-generation autonomous AI to automate unit testing, freeing up developers to focus on more creative work. Diffblue Cover can write a complete and correct Java unit test every 2 seconds, and it is directly integrated into CI pipelines, unlike AI-powered code suggestions that require developers to check the code for bugs. Diffblue Cover is trusted by the world's leading organizations, including Goldman Sachs, and has been proven to improve quality, lower developer effort, help with code understanding, reduce risk, and increase deployment frequency.

Recognito is a leading facial recognition technology provider, offering the NIST FRVT Top 1 Face Recognition Algorithm. Their high-performance biometric technology is used by police forces and security services to enhance public safety, manage individual movements, and improve audience analytics for businesses. Recognito's software goes beyond object detection to provide detailed user role descriptions and develop user flows. The application enables rapid face and body attribute recognition, video analytics, and artificial intelligence analysis. With a focus on security, living, and business improvements, Recognito helps create safer and more prosperous cities.

Kickresume is an online resume and cover letter builder that uses artificial intelligence to help users create professional-looking documents. The website offers a variety of templates and tools to help users customize their resumes and cover letters, and it also provides feedback on the user's writing. Kickresume is a valuable tool for anyone who is looking to improve their job search prospects.

Comet Opik is a repository containing two main services: a frontend and a backend. It provides a Python SDK for easy installation. Users can run the full application locally with minikube, following specific installation prerequisites. The repository structure includes directories for applications like Opik backend, with detailed instructions available in the README files. Users can manage the installation using simple k8s commands and interact with the application via URLs for checking the running application and API documentation. The repository aims to facilitate local development and testing of Opik using Kubernetes technology.

EDA GPT is an open-source data analysis companion that offers a comprehensive solution for structured and unstructured data analysis. It streamlines the data analysis process, empowering users to explore, visualize, and gain insights from their data. EDA GPT supports analyzing structured data in various formats like CSV, XLSX, and SQLite, generating graphs, and conducting in-depth analysis of unstructured data such as PDFs and images. It provides a user-friendly interface, powerful features, and capabilities like comparing performance with other tools, analyzing large language models, multimodal search, data cleaning, and editing. The tool is optimized for maximal parallel processing, searching internet and documents, and creating analysis reports from structured and unstructured data.

ModelScope-Agent is a customizable and scalable Agent framework. A single agent has abilities such as role-playing, LLM calling, tool usage, planning, and memory. It mainly has the following characteristics: - **Simple Agent Implementation Process**: Simply specify the role instruction, LLM name, and tool name list to implement an Agent application. The framework automatically arranges workflows for tool usage, planning, and memory. - **Rich models and tools**: The framework is equipped with rich LLM interfaces, such as Dashscope and Modelscope model interfaces, OpenAI model interfaces, etc. Built in rich tools, such as **code interpreter**, **weather query**, **text to image**, **web browsing**, etc., make it easy to customize exclusive agents. - **Unified interface and high scalability**: The framework has clear tools and LLM registration mechanism, making it convenient for users to expand more diverse Agent applications. - **Low coupling**: Developers can easily use built-in tools, LLM, memory, and other components without the need to bind higher-level agents.

LLM-Minutes-of-Meeting is a project showcasing NLP & LLM's capability to summarize long meetings and automate the task of delegating Minutes of Meeting(MoM) emails. It converts audio/video files to text, generates editable MoM, and aims to develop a real-time python web-application for meeting automation. The tool features keyword highlighting, topic tagging, export in various formats, user-friendly interface, and uses Celery for asynchronous processing. It is designed for corporate meetings, educational institutions, legal and medical fields, accessibility, and event coverage.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

pgvecto.rs is a Postgres extension written in Rust that provides vector similarity search functions. It offers ultra-low-latency, high-precision vector search capabilities, including sparse vector search and full-text search. With complete SQL support, async indexing, and easy data management, it simplifies data handling. The extension supports various data types like FP16/INT8, binary vectors, and Matryoshka embeddings. It ensures system performance with production-ready features, high availability, and resource efficiency. Security and permissions are managed through easy access control. The tool allows users to create tables with vector columns, insert vector data, and calculate distances between vectors using different operators. It also supports half-precision floating-point numbers for better performance and memory usage optimization.

formsflow.ai is a Free, Open-Source, Low Code Development Platform for rapidly building powerful business applications. It combines leading Open-Source applications including form.io forms, Camunda’s workflow engine, Keycloak’s security, and Redash’s data analytics into a seamless, integrated platform. Check out the installation documentation for installation instructions and features documentation to explore features and capabilities in detail.

Jarvis Version 3 is a versatile personal assistant application designed to enhance productivity by automating common tasks. It can interact with websites and applications, perform searches, manage device functions, and control music. Users can give commands to open websites, search on Google or YouTube, scroll pages, manage applications, check time, internet speed, battery percentage, battery alerts, charging status, play music, and synchronize clapping with music. The tool offers features for web navigation, search functionality, scrolling, application management, device management, and music control.

OpenNARS-for-Applications is an implementation of a Non-Axiomatic Reasoning System, a general-purpose reasoner that adapts under the Assumption of Insufficient Knowledge and Resources. The system combines the logic and conceptual ideas of OpenNARS, event handling and procedure learning capabilities of ANSNA and 20NAR1, and the control model from ALANN. It is written in C, offers improved reasoning performance, and has been compared with Reinforcement Learning and means-end reasoning approaches. The system has been used in real-world applications such as assisting first responders, real-time traffic surveillance, and experiments with autonomous robots. It has been developed with a pragmatic mindset focusing on effective implementation of existing theory.

Guardrails is a Python framework that helps build reliable AI applications by performing two key functions: 1. Guardrails runs Input/Output Guards in your application that detect, quantify and mitigate the presence of specific types of risks. To look at the full suite of risks, check out Guardrails Hub. 2. Guardrails help you generate structured data from LLMs.

This repository contains community-driven practical examples of building AI applications and solving various tasks with AI using open-source tools and models. Everyone is welcome to contribute, and we value everybody's contribution! There are several ways you can contribute to the Open-Source AI Cookbook: Submit an idea for a desired example/guide via GitHub Issues. Contribute a new notebook with a practical example. Improve existing examples by fixing issues/typos. Before contributing, check currently open issues and pull requests to avoid working on something that someone else is already working on.

Vectara Answer is a sample app for Vectara-powered Summarized Semantic Search (or question-answering) with advanced configuration options. For examples of what you can build with Vectara Answer, check out Ask News, LegalAid, or any of the other demo applications.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

A simple and convenient interface for using various neural network models. Users can interact with LLM using text, voice, and image input to generate images, videos, 3D objects, music, and audio. The tool supports a wide range of models for different tasks such as image generation, video generation, audio file separation, voice conversion, and more. Users can also view files from the outputs directory in a gallery, download models, change application settings, and check system sensors. The goal of the project is to create an easy-to-use application for utilizing neural network models.

**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.

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.

LangStream is a tool for natural language processing tasks, providing a CLI for easy installation and usage. Users can try sample applications like Chat Completions and create their own applications using the developer documentation. It supports running on Kubernetes for production-ready deployment, with support for various Kubernetes distributions and external components like Apache Kafka or Apache Pulsar cluster. Users can deploy LangStream locally using minikube and manage the cluster with mini-langstream. Development requirements include Docker, Java 17, Git, Python 3.11+, and PIP, with the option to test local code changes using mini-langstream.

This repository contains an early-phase IREE compiler and runtime plugin for interfacing the AMD AIE accelerator to IREE. It provides architectural overview, developer setup instructions, building guidelines, and runtime driver setup details. The repository focuses on enabling the integration of the AMD AIE accelerator with IREE, offering developers the tools and resources needed to build and run applications leveraging this technology.

UFO is a UI-focused dual-agent framework to fulfill user requests on Windows OS by seamlessly navigating and operating within individual or spanning multiple applications.

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Professional H1B Visa Assistant: Ask any questions you have regarding H1B visa including application, day 1 CPT, etc.

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Career Catalyst is an AI-powered assistant specializing in job application support, adept at enhancing CVs and cover letters by aligning them with specific job descriptions for a standout application.

Expert in drafting recommendation letters for U.S. green card application under EB-1A and EB2-NIW applications. Please start from the conversation starters but with the info of yourself.

Le GPT custom de Sclépios IA analyse les ordonnances et répond aux interrogations sur les médicaments rapidement et avec précision. Visitez sclepios-mobile.com pour plus d'informations et pour accéder à l'application mobile.

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