Best AI tools for< Check Domain Ownership >
20 - AI tool Sites
Atai.world
Atai.world is a website domain that appears to be registered but available for purchase. The site does not provide any specific information or functionality, and it seems to be related to privacy settings and technical support. The website is available in English language.
Heissdocs
Heissdocs.com is a domain selling platform that offers a secure and hassle-free process for buying and transferring domain names. The platform ensures buyer protection through a unique program, fast and easy transfers, and secure payment options. It provides information on Value Added Tax (VAT) for EU consumers and businesses. With a focus on simplicity and safety, Heissdocs.com aims to make domain name transactions straightforward and secure for users.
Ponzu.gg
Ponzu.gg is a domain name that may be for sale. The website provides information about the domain and offers the option to inquire about purchasing it. It is a platform where users can explore the availability of the domain name and potentially acquire it for their own use. The site emphasizes copyright and privacy policy to protect intellectual property rights and user data.
Sttabot.io
Sttabot.io is a domain parking webpage generated by the domain owner using Sedo. The website provides resources and information related to the domain name. Visitors can find out if the domain name is for sale or contact the domain owner for inquiries. The webpage also includes a disclaimer stating that Sedo, the platform used for domain parking, does not have a relationship with third-party advertisers and does not control or endorse any specific service or trademark mentioned on the page.
Namy.ai
Namy.ai is a domain generator that uses AI technology to help users quickly create website domain names. Users can describe their business or idea, and the tool generates domain suggestions in just 30 seconds. The tool also allows users to check domain availability and browse pre-generated domain options. With Namy.ai, users can easily find the perfect domain name for their business or project.
Namewizard
Namewizard is an AI-powered domain name generator that helps you find the perfect domain name for your business or project. With Namewizard, you can generate unlimited domain name suggestions, check domain availability, and use advanced search filters to narrow down your results. Namewizard also offers a history of your domain name suggestions so you can easily track your progress. Namewizard is the perfect tool for anyone who is looking for a creative and unique domain name.
SearchLoom
SearchLoom is an AI-powered domain name generator that revolutionizes the process of finding the perfect domain name for your business or idea. By harnessing the power of artificial intelligence, SearchLoom generates creative and context-aware domain suggestions that align with your brand's identity and goals. The advanced AI technology analyzes your business description and industry context to provide intelligent domain recommendations across multiple TLDs, ensuring availability and relevance. With features like real-time availability checks, smart recommendations, and instant AI generation, SearchLoom offers a seamless and efficient domain search experience for modern businesses.
jsontochatgpt.com
jsontochatgpt.com is a domain available for purchase on GoDaddy Auctions. The website provides information about the domain and its availability for interested buyers. It is not an AI tool or application, but rather a platform for domain transactions and auctions.
Contentcale
Contentcale.com is a domain currently up for sale. The website serves as a platform for selling the domain and provides information about the domain. It is generated by Sedo Domain Parking, and the site disclaims any relationship with third-party advertisers. The contentcale.com domain may be purchased by interested parties.
Posturenet.app
Posturenet.app is a website that appears to be a domain parking page created by Sedo. The site provides information about posturenet resources and may offer the domain name for sale. It seems to be a platform for domain owners to park their domains and potentially sell them. The webpage includes a disclaimer stating that Sedo, the platform used for domain parking, does not have a relationship with third-party advertisers and does not endorse or recommend any specific services or trademarks. Additionally, a privacy policy is mentioned on the page.
Namify
Namify is an AI-powered business name generator that helps users create a memorable brand name effortlessly. It leverages the power of new domain extensions to curate meaningful domain name suggestions for various businesses. Namify also provides logo design options and checks domain name, social media username, and trademark availability to ensure a solid branding decision. With expert recommendations and a user-friendly interface, Namify streamlines the process of finding the perfect brand name for your business.
Brandix
Brandix is an AI-powered tool that helps users generate brand names in seconds. Users can input their ideas or choose from various categories to receive the perfect brand name. Additionally, the tool instantly checks the domain availability for the generated names. With a user-friendly interface, Brandix has assisted thousands of people in finding the ideal brand name for their businesses.
SmartyNames.com
SmartyNames.com is a business name generator that uses AI to help entrepreneurs come up with creative and unique names for their businesses. The tool is easy to use and provides instant results. It also offers a variety of features to help users find the perfect name for their business, including a domain name checker and a reverse domain search. SmartyNames.com is a valuable tool for any entrepreneur who is looking for a unique and memorable name for their business.
NamePepper
NamePepper is a free AI business name generator tool that helps users unlock brandable names for their businesses. The tool generates hundreds of creative and iconic business names tailored to the user's preferences and industry. Users can quickly check domain availability, save favorite names, and get feedback from others. NamePepper aims to simplify the naming process and save users time and effort in creating a memorable brand identity.
GoDaddy Domain Sale Page
The website appears to be a domain for sale page hosted by GoDaddy. It seems that the domain 'ikigai.quest' is listed for sale on this page. Users are denied access to the content of the page with an 'Access Denied' message. The page also includes a reference number for the denied access error.
Chainintel.info
Chainintel.info is a website that appears to be a domain for sale. The site simply states 'chainintel.info Buy this domain. 2024 Copyright. All Rights Reserved. Privacy Policy'. It seems to be a platform for purchasing the domain name 'chainintel.info'. The website does not provide any additional information or services beyond the domain sale.
vnsplit.me
vnsplit.me is a domain for sale website that offers the domain 'vnsplit.me' for purchase. The website is copyright protected until 2024 and all rights are reserved. It also has a privacy policy in place to protect user data and information.
Emaildojo
Emaildojo is an AI-driven email innovation hub that provides free and unique email tools to help users elevate their email game. With Emaildojo, users can generate catchy and innovative short-form content, prevent their emails from landing in spam, boost ROI by driving clicks from email inbox, detect, analyze, and fix email domain issues, and check, lookup, and validate their email identity instantly. Emaildojo is the perfect tool for email marketers who want to improve their email deliverability and engagement.
OpenFuture
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.
BluePond GenAI PaaS
BluePond GenAI PaaS is an automation and insights powerhouse tailored for Property and Casualty Insurance. It offers end-to-end execution support from GenAI data scientists, engineers & human-in-the-loop processing. The platform provides automated intake extraction, classification enrichment, validation, complex document analysis, workflow automation, and decisioning. Users benefit from rapid deployment, complete control of data & IP, and pre-trained P&C domain library. BluePond GenAI PaaS aims to energize and expedite GenAI initiatives throughout the insurance value chain.
20 - Open Source AI Tools
argilla
Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency. It helps users improve AI output quality through data quality, take control of their data and models, and improve efficiency by quickly iterating on the right data and models. Argilla is an open-source community-driven project that provides tools for achieving and maintaining high-quality data standards, with a focus on NLP and LLMs. It is used by AI teams from companies like the Red Cross, Loris.ai, and Prolific to improve the quality and efficiency of AI projects.
upgini
Upgini is an intelligent data search engine with a Python library that helps users find and add relevant features to their ML pipeline from various public, community, and premium external data sources. It automates the optimization of connected data sources by generating an optimal set of machine learning features using large language models, GraphNNs, and recurrent neural networks. The tool aims to simplify feature search and enrichment for external data to make it a standard approach in machine learning pipelines. It democratizes access to data sources for the data science community.
crawl4ai
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.
awesome-synthetic-datasets
This repository focuses on organizing resources for building synthetic datasets using large language models. It covers important datasets, libraries, tools, tutorials, and papers related to synthetic data generation. The goal is to provide pragmatic and practical resources for individuals interested in creating synthetic datasets for machine learning applications.
AITreasureBox
AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.
prompt-tuning-playbook
The LLM Prompt Tuning Playbook is a comprehensive guide for improving the performance of post-trained Language Models (LLMs) through effective prompting strategies. It covers topics such as pre-training vs. post-training, considerations for prompting, a rudimentary style guide for prompts, and a procedure for iterating on new system instructions. The playbook emphasizes the importance of clear, concise, and explicit instructions to guide LLMs in generating desired outputs. It also highlights the iterative nature of prompt development and the need for systematic evaluation of model responses.
awesome-artificial-intelligence-guidelines
The 'Awesome AI Guidelines' repository aims to simplify the ecosystem of guidelines, principles, codes of ethics, standards, and regulations around artificial intelligence. It provides a comprehensive collection of resources addressing ethical and societal challenges in AI systems, including high-level frameworks, principles, processes, checklists, interactive tools, industry standards initiatives, online courses, research, and industry newsletters, as well as regulations and policies from various countries. The repository serves as a valuable reference for individuals and teams designing, building, and operating AI systems to navigate the complex landscape of AI ethics and governance.
ail-typo-squatting
ail-typo-squatting is a Python library designed to generate a list of potential typo squatting domains using a domain name permutation engine. It can be used as a standalone tool or to feed other systems. The tool provides various algorithms to create typos by adding, changing, or omitting characters in domain names. It also offers DNS resolving capabilities to check the availability of generated variations. The project has been co-funded by CEF-TC-2020-2 - 2020-EU-IA-0260 - JTAN - Joint Threat Analysis Network.
deepdoctection
**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.
airflow-chart
This Helm chart bootstraps an Airflow deployment on a Kubernetes cluster using the Helm package manager. The version of this chart does not correlate to any other component. Users should not expect feature parity between OSS airflow chart and the Astronomer airflow-chart for identical version numbers. To install this helm chart remotely (using helm 3) kubectl create namespace airflow helm repo add astronomer https://helm.astronomer.io helm install airflow --namespace airflow astronomer/airflow To install this repository from source sh kubectl create namespace airflow helm install --namespace airflow . Prerequisites: Kubernetes 1.12+ Helm 3.6+ PV provisioner support in the underlying infrastructure Installing the Chart: sh helm install --name my-release . The command deploys Airflow on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation. Upgrading the Chart: First, look at the updating documentation to identify any backwards-incompatible changes. To upgrade the chart with the release name `my-release`: sh helm upgrade --name my-release . Uninstalling the Chart: To uninstall/delete the `my-release` deployment: sh helm delete my-release The command removes all the Kubernetes components associated with the chart and deletes the release. Updating DAGs: Bake DAGs in Docker image The recommended way to update your DAGs with this chart is to build a new docker image with the latest code (`docker build -t my-company/airflow:8a0da78 .`), push it to an accessible registry (`docker push my-company/airflow:8a0da78`), then update the Airflow pods with that image: sh helm upgrade my-release . --set images.airflow.repository=my-company/airflow --set images.airflow.tag=8a0da78 Docker Images: The Airflow image that are referenced as the default values in this chart are generated from this repository: https://github.com/astronomer/ap-airflow. Other non-airflow images used in this chart are generated from this repository: https://github.com/astronomer/ap-vendor. Parameters: The complete list of parameters supported by the community chart can be found on the Parameteres Reference page, and can be set under the `airflow` key in this chart. The following tables lists the configurable parameters of the Astronomer chart and their default values. | Parameter | Description | Default | | :----------------------------- | :-------------------------------------------------------------------------------------------------------- | :---------------------------- | | `ingress.enabled` | Enable Kubernetes Ingress support | `false` | | `ingress.acme` | Add acme annotations to Ingress object | `false` | | `ingress.tlsSecretName` | Name of secret that contains a TLS secret | `~` | | `ingress.webserverAnnotations` | Annotations added to Webserver Ingress object | `{}` | | `ingress.flowerAnnotations` | Annotations added to Flower Ingress object | `{}` | | `ingress.baseDomain` | Base domain for VHOSTs | `~` | | `ingress.auth.enabled` | Enable auth with Astronomer Platform | `true` | | `extraObjects` | Extra K8s Objects to deploy (these are passed through `tpl`). More about Extra Objects. | `[]` | | `sccEnabled` | Enable security context constraints required for OpenShift | `false` | | `authSidecar.enabled` | Enable authSidecar | `false` | | `authSidecar.repository` | The image for the auth sidecar proxy | `nginxinc/nginx-unprivileged` | | `authSidecar.tag` | The image tag for the auth sidecar proxy | `stable` | | `authSidecar.pullPolicy` | The K8s pullPolicy for the the auth sidecar proxy image | `IfNotPresent` | | `authSidecar.port` | The port the auth sidecar exposes | `8084` | | `gitSyncRelay.enabled` | Enables git sync relay feature. | `False` | | `gitSyncRelay.repo.url` | Upstream URL to the git repo to clone. | `~` | | `gitSyncRelay.repo.branch` | Branch of the upstream git repo to checkout. | `main` | | `gitSyncRelay.repo.depth` | How many revisions to check out. Leave as default `1` except in dev where history is needed. | `1` | | `gitSyncRelay.repo.wait` | Seconds to wait before pulling from the upstream remote. | `60` | | `gitSyncRelay.repo.subPath` | Path to the dags directory within the git repository. | `~` | Specify each parameter using the `--set key=value[,key=value]` argument to `helm install`. For example, sh helm install --name my-release --set executor=CeleryExecutor --set enablePodLaunching=false . Walkthrough using kind: Install kind, and create a cluster We recommend testing with Kubernetes 1.25+, example: sh kind create cluster --image kindest/node:v1.25.11 Confirm it's up: sh kubectl cluster-info --context kind-kind Add Astronomer's Helm repo sh helm repo add astronomer https://helm.astronomer.io helm repo update Create namespace + install the chart sh kubectl create namespace airflow helm install airflow -n airflow astronomer/airflow It may take a few minutes. Confirm the pods are up: sh kubectl get pods --all-namespaces helm list -n airflow Run `kubectl port-forward svc/airflow-webserver 8080:8080 -n airflow` to port-forward the Airflow UI to http://localhost:8080/ to confirm Airflow is working. Login as _admin_ and password _admin_. Build a Docker image from your DAGs: 1. Start a project using astro-cli, which will generate a Dockerfile, and load your DAGs in. You can test locally before pushing to kind with `astro airflow start`. `sh mkdir my-airflow-project && cd my-airflow-project astro dev init` 2. Then build the image: `sh docker build -t my-dags:0.0.1 .` 3. Load the image into kind: `sh kind load docker-image my-dags:0.0.1` 4. Upgrade Helm deployment: sh helm upgrade airflow -n airflow --set images.airflow.repository=my-dags --set images.airflow.tag=0.0.1 astronomer/airflow Extra Objects: This chart can deploy extra Kubernetes objects (assuming the role used by Helm can manage them). For Astronomer Cloud and Enterprise, the role permissions can be found in the Commander role. yaml extraObjects: - apiVersion: batch/v1beta1 kind: CronJob metadata: name: "{{ .Release.Name }}-somejob" spec: schedule: "*/10 * * * *" concurrencyPolicy: Forbid jobTemplate: spec: template: spec: containers: - name: myjob image: ubuntu command: - echo args: - hello restartPolicy: OnFailure Contributing: Check out our contributing guide! License: Apache 2.0 with Commons Clause
vscode-pddl
The vscode-pddl extension provides comprehensive support for Planning Domain Description Language (PDDL) in Visual Studio Code. It enables users to model planning domains, validate them, industrialize planning solutions, and run planners. The extension offers features like syntax highlighting, auto-completion, plan visualization, plan validation, plan happenings evaluation, search debugging, and integration with Planning.Domains. Users can create PDDL files, run planners, visualize plans, and debug search algorithms efficiently within VS Code.
llama-recipes
The llama-recipes repository provides a scalable library for fine-tuning Llama 2, along with example scripts and notebooks to quickly get started with using the Llama 2 models in a variety of use-cases, including fine-tuning for domain adaptation and building LLM-based applications with Llama 2 and other tools in the LLM ecosystem. The examples here showcase how to run Llama 2 locally, in the cloud, and on-prem.
NightshadeAntidote
Nightshade Antidote is an image forensics tool used to analyze digital images for signs of manipulation or forgery. It implements several common techniques used in image forensics including metadata analysis, copy-move forgery detection, frequency domain analysis, and JPEG compression artifacts analysis. The tool takes an input image, performs analysis using the above techniques, and outputs a report summarizing the findings.
aiwechat-vercel
aiwechat-vercel is a tool that integrates AI capabilities into WeChat public accounts using Vercel functions. It requires minimal server setup, low entry barriers, and only needs a domain name that can be bound to Vercel, with almost zero cost. The tool supports various AI models, continuous Q&A sessions, chat functionality, system prompts, and custom commands. It aims to provide a platform for learning and experimentation with AI integration in WeChat public accounts.
yet-another-applied-llm-benchmark
Yet Another Applied LLM Benchmark is a collection of diverse tests designed to evaluate the capabilities of language models in performing real-world tasks. The benchmark includes tests such as converting code, decompiling bytecode, explaining minified JavaScript, identifying encoding formats, writing parsers, and generating SQL queries. It features a dataflow domain-specific language for easily adding new tests and has nearly 100 tests based on actual scenarios encountered when working with language models. The benchmark aims to assess whether models can effectively handle tasks that users genuinely care about.
farel-bench
The 'farel-bench' project is a benchmark tool for testing LLM reasoning abilities with family relationship quizzes. It generates quizzes based on family relationships of varying degrees and measures the accuracy of large language models in solving these quizzes. The project provides scripts for generating quizzes, running models locally or via APIs, and calculating benchmark metrics. The quizzes are designed to test logical reasoning skills using family relationship concepts, with the goal of evaluating the performance of language models in this specific domain.
BehaviorTree.CPP
BehaviorTree.CPP is a C++ 17 library that provides a framework to create BehaviorTrees. It was designed to be flexible, easy to use, reactive and fast. Even if our main use-case is robotics, you can use this library to build AI for games, or to replace Finite State Machines. There are few features which make BehaviorTree.CPP unique, when compared to other implementations: It makes asynchronous Actions, i.e. non-blocking, a first-class citizen. You can build reactive behaviors that execute multiple Actions concurrently (orthogonality). Trees are defined using a Domain Specific scripting language (based on XML), and can be loaded at run-time; in other words, even if written in C++, the morphology of the Trees is not hard-coded. You can statically link your custom TreeNodes or convert them into plugins and load them at run-time. It provides a type-safe and flexible mechanism to do Dataflow between Nodes of the Tree. It includes a logging/profiling infrastructure that allows the user to visualize, record, replay and analyze state transitions.
20 - OpenAI Gpts
Brand Genius GPT
A branding expert for all business types, specializing in creative names and domain checks.
Website Value Appraisal Tool - Value My Website
Website Value Appraisal Tool - Value My Website. I'm a checker and calculator tool for appraising the value and worth of websites, estimating prices based on domain & website's daily, monthly, annual revenue.
Credit Score Check
Guides on checking and monitoring credit scores, with a financial and informative tone.
Backloger.ai - Requirements Health Check
Drop in any requirements ; I'll reduces ambiguity using requirement health check
Website Worth Calculator - Check Website Value
Calculate website worth by analyzing monthly revenue, using industry-standard valuation methods to provide approximate, informative value estimates.
News Bias Corrector
Balances out bias and researches live reports to give you a more balanced view (Paste in the text you want to check)
Service Rater
Helps check and provide feedback on service providers like contractors and plumbers.
Are You Weather Dependent or Not?
A mental health self-check tool assessing weather dependency. Powered by WeatherMind
AI Essay Writer
ChatGPT Essay Writer helps you to write essays with OpenAI. Generate Professional Essays with Plagiarism Check, Formatting, Cost Estimation & More.