Best AI tools for< Identify Users >

Dog Identifier is an AI-based application that helps users identify over 170+ dog breeds by simply providing an image or video of a dog. The app predicts the breed of the dog and provides detailed information about characteristics, temperament, and history of the breed. Users can also search for their ideal furry companion by answering a few lifestyle-related questions. Additionally, the app features a comprehensive database of dog breeds, daily fun facts, and a new Dog Mood Detection feature that analyzes a dog's facial expressions and body language to suggest their mood.

The Cat Identifier is an AI-powered application designed to help users identify different cat breeds accurately and efficiently. By simply uploading a picture of a cat, the app uses advanced image recognition technology to analyze key features and provide the most likely breed match. With a user-friendly interface, the Cat Identifier is suitable for both cat enthusiasts and professionals in the pet industry.

The website offers a free AI-powered tool that helps users identify dog breeds by uploading a photo of their dog. The tool analyzes key physical attributes of the dog, such as ear shape, muzzle length, fur pattern, and body size, comparing them against a database of known dog breeds to provide an accurate breed determination. Users can maximize accuracy by following simple scanning tips provided on the site. The tool prioritizes user privacy by not storing uploaded photos permanently and ensuring they are used only for analysis purposes.

Tome is an AI assistant designed specifically for sales professionals. It acts as a second brain, leveraging AI to analyze playbook and CRM data to help users identify strategic initiatives, key decision makers, and accounts that matter. With features like pinpointing accounts with growth indicators, understanding company financials, and crafting personalized outreach, Tome aims to enhance sales effectiveness and efficiency.

ZeroGPT is a comprehensive AI detection tool that helps users identify AI-generated content. It offers a range of features, including sentence highlighting, batch file upload, high accuracy, and support for multiple languages. ZeroGPT's DeepAnalyse™ Technology employs a multi-stage methodology to analyze text and determine its origin. The tool is designed to minimize false positives and negatives, providing users with reliable results. ZeroGPT also offers a user-friendly API for organizations, enabling them to integrate the tool into their systems.

SkyHive is an AI-powered platform that aims to organize the world's workforce data and facilitate reskilling. It offers solutions for businesses, governments, educators, and individuals to leverage skills-based models, automate processes, and drive employee engagement. SkyHive's technology utilizes advanced skills matching algorithms, real-time labor market data, and predictive analytics to help users identify skill gaps, connect to opportunities, and accelerate career advancement.

Winston AI is a leading AI content detection tool designed to help users identify AI-generated text from ChatGPT, GPT-4, Google Bard, and other large language models. It offers a range of features, including AI content detection, plagiarism checking, readability scoring, and OCR (Optical Character Recognition) technology for extracting text from scanned documents or pictures. Winston AI is committed to providing accurate and reliable AI detection, with a 99.98% accuracy rate and continuous updates to keep up with the latest advancements in AI writing tools.

The GPT-2 Output Detector is an online tool that helps users identify whether a given text was generated by the GPT-2 language model. The tool is based on the RoBERTa implementation of Transformers, a popular natural language processing library. Users can enter text into the text box, and the tool will predict the probability that the text was generated by GPT-2. The results start to get reliable after around 50 tokens.

Pyrafect is an AI tool that combines AI and risk-based analysis to help users identify high-risk issues and streamline bug fixes. By leveraging AI technology, Pyrafect aims to assist users in prioritizing tasks and delivering a stable user experience. The tool offers early access to its features, allowing users to proactively manage risks and focus on what matters most.

Hiya is an AI-powered caller ID, call blocker, and protection application that enhances voice communication experiences. It helps users identify incoming calls, block spam and fraud, and protect against AI voice fraud and scams. Hiya offers solutions for businesses, carriers, and consumers, with features like branded caller ID, spam detection, call filtering, and more. With a global reach and a user base of over 450 million, Hiya aims to bring trust, identity, and intelligence back to phone calls.

Connecterra is an intelligent data platform designed specifically for the dairy industry. It provides farmers, advisors, and enterprises with a comprehensive suite of tools to collect, analyze, and visualize their farm data. With advanced AI capabilities, Connecterra helps users identify trends, optimize decision-making, and improve overall farm performance.

Saifr is an AI-powered marketing compliance solution that simplifies compliance reviews and content creation processes. With accurate data and decades of insights, Saifr's AI technology helps users identify compliance risks, propose alternative phrasing, and streamline compliance workflows. The platform aims to enhance operational efficiency, safeguard against risks, and make compliance reviews more efficient for users to focus on creative work.

Connecterra is an intelligent data platform designed specifically for the dairy industry. It provides farmers, advisors, and enterprises with a comprehensive suite of tools to collect, analyze, and visualize their farm data. With advanced AI capabilities, Connecterra helps users identify trends, make informed decisions, and improve their overall operational efficiency.

AI Detector is an online tool that uses advanced algorithms and machine learning to check if your written text is generated by AI or a human writer. It analyzes the writing style, sentence structure, and other linguistic patterns to determine the likelihood of AI authorship. The tool provides a percentage score indicating the probability of AI-generated content, helping users identify potential plagiarism or AI-assisted writing.

ZeroGPT is a free AI content detector that helps users identify AI-generated text. It uses machine learning algorithms and natural language processing techniques to analyze text and determine whether it was written by a human or an AI. ZeroGPT is accurate, fast, and easy to use. It can be used to detect AI-generated text in a variety of languages, including English, Spanish, French, German, and Chinese. ZeroGPT is a valuable tool for anyone who wants to ensure that their content is original and authentic.

Ai-SPY is an advanced AI audio detection tool that helps users identify whether speech is human or AI-generated. It offers detailed reports, easy integration with API access, and expert human insights for accurate analysis. Users can upload audio files or analyze social media links to determine authenticity. Ai-SPY leverages a proprietary neural network for unparalleled audio authenticity insights, making it a valuable tool for content verification and enterprise use.

Melon is an AI-powered tool that helps users learn and think more effectively. It allows users to save, organize, and visualize their learning from various sources, including articles, LinkedIn posts, tweets, and YouTube videos. Melon's AI brain can retrieve, summarize, and connect insights from saved content, helping users identify patterns and correlations that might not be immediately apparent to them. Users can also create collections to group saved content based on topic, focus, or area of interest.

ROAST is an AI-powered dating profile review service that helps users optimize their profiles to get more matches. The service uses data-driven insights and expert advice to provide personalized feedback on users' photos, bios, and overall profile strategy. ROAST also offers a quiz that helps users identify their dating goals and provides tailored advice based on their answers.

Qualifier.ai is an AI tool that automates outbound sales via email, helping users identify the best prospects, find contact details, send emails at the right time, and nurture leads through automated campaigns. It is designed to increase revenue by streamlining the sales process and enhancing prospecting efforts. The tool offers smart targeting, email automation, and nurture campaigns to optimize sales potential and improve lead generation. With advanced algorithms and integration capabilities, Qualifier.ai provides a user-friendly experience for businesses looking to boost their sales performance.

Ignition is an AI-powered roadmapping suite designed to connect roadmaps to revenue. It helps users identify and prioritize feature gaps based on revenue impact, generate roadmaps, and align them with Sales effortlessly. The tool automates the process of building revenue-based roadmaps, extracting deal-blocking feature gaps, and notifying sales reps when features ship. With AI analysis, users can surface key themes from customer conversations, prioritize roadmap items, and quantify the product's impact on revenue. Ignition aims to empower sales teams, automate product operations, and improve adoption and revenue impact.

CredSweeper is a tool designed to detect credentials like tokens, passwords, and API keys in directories or files. It helps users identify potential exposure of sensitive information by scanning lines, filtering, and utilizing an AI model. The tool reports lines containing possible credentials, their location, and the expected type of credential.

SuperBench is a validation and profiling tool for AI infrastructure. It provides a comprehensive set of tests and benchmarks to evaluate the performance and reliability of AI systems. The tool helps users identify bottlenecks, optimize configurations, and ensure the stability of their AI infrastructure. SuperBench is designed to streamline the validation process and improve the overall efficiency of AI deployments.

Algolisted is a pioneering platform dedicated to algorithmic problem-solving, offering a centralized hub for a diverse array of algorithmic challenges. It provides an immersive online environment for programmers to enhance their skills through Data Structures and Algorithms (DSA) sheets, academic progress tracking, resume refinement with OpenAI integration, adaptive testing, and job opportunity listings. The project is built on the MERN stack, Flask, Beautiful Soup, and Selenium,GEN AI, and deployed on Firebase. Algolisted aims to be a reliable companion in the pursuit of coding knowledge and proficiency.

Mutahunter is an open-source language-agnostic mutation testing tool maintained by CodeIntegrity. It leverages LLM models to inject context-aware faults into codebase, ensuring comprehensive testing. The tool aims to empower companies and developers to enhance test suites and improve software quality by verifying the effectiveness of test cases through creating mutants in the code and checking if the test cases can catch these changes. Mutahunter provides detailed reports on mutation coverage, killed mutants, and survived mutants, enabling users to identify potential weaknesses in their test suites.

The Intelligence Toolkit is a suite of interactive workflows designed to help domain experts make sense of real-world data by identifying patterns, themes, relationships, and risks within complex datasets. It utilizes generative AI (GPT models) to create reports on findings of interest. The toolkit supports analysis of case, entity, and text data, providing various interactive workflows for different intelligence tasks. Users are expected to evaluate the quality of data insights and AI interpretations before taking action. The system is designed for moderate-sized datasets and responsible use of personal case data. It uses the GPT-4 model from OpenAI or Azure OpenAI APIs for generating reports and insights.

LightRAG is a repository hosting the code for LightRAG, a system that supports seamless integration of custom knowledge graphs, Oracle Database 23ai, Neo4J for storage, and multiple file types. It includes features like entity deletion, batch insert, incremental insert, and graph visualization. LightRAG provides an API server implementation for RESTful API access to RAG operations, allowing users to interact with it through HTTP requests. The repository also includes evaluation scripts, code for reproducing results, and a comprehensive code structure.

OpenGlass is an open-source project that allows users to transform any regular glasses into smart glasses using affordable off-the-shelf components. With a cost of less than $25, users can enhance their glasses to record their daily activities, recognize people, identify objects, translate text, and more. The project provides detailed instructions on hardware setup and software installation, making it accessible for DIY enthusiasts and tech enthusiasts alike. By following the steps outlined in the repository, users can create their own smart glasses and explore various functionalities offered by the project.

Build-your-own-AI-Assistant-Solution-Accelerator is a pre-release and preview solution that helps users create their own AI assistants. It leverages Azure Open AI Service, Azure AI Search, and Microsoft Fabric to identify, summarize, and categorize unstructured information. Users can easily find relevant articles and grants, generate grant applications, and export them as PDF or Word documents. The solution accelerator provides reusable architecture and code snippets for building AI assistants with enterprise data. It is designed for researchers looking to explore flu vaccine studies and grants to accelerate grant proposal submissions.

LLMFarm is an iOS and MacOS app designed to work with large language models (LLM). It allows users to load different LLMs with specific parameters, test the performance of various LLMs on iOS and macOS, and identify the most suitable model for their projects. The tool is based on ggml and llama.cpp by Georgi Gerganov and incorporates sources from rwkv.cpp by saharNooby, Mia by byroneverson, and LlamaChat by alexrozanski. LLMFarm features support for MacOS (13+) and iOS (16+), various inferences and sampling methods, Metal compatibility (not supported on Intel Mac), model setting templates, LoRA adapters support, LoRA finetune support, LoRA export as model support, and more. It also offers a range of inferences including LLaMA, GPTNeoX, Replit, GPT2, Starcoder, RWKV, Falcon, MPT, Bloom, and others. Additionally, it supports multimodal models like LLaVA, Obsidian, and MobileVLM. Users can customize inference options through JSON files and access supported models for download.

This repository contains a vulnerability mining engine based on GPT technology. The engine is designed to identify logic vulnerabilities in code by utilizing task-driven prompts. It does not require prior knowledge or fine-tuning and focuses on prompt design rather than model design. The tool is effective in real-world projects and should not be used for academic vulnerability testing. It supports scanning projects in various languages, with current support for Solidity. The engine is configured through prompts and environment settings, enabling users to scan for vulnerabilities in their codebase. Future updates aim to optimize code structure, add more language support, and enhance usability through command line mode. The tool has received a significant audit bounty of $50,000+ as of May 2024.

FiftyOne is an open-source tool designed for building high-quality datasets and computer vision models. It supercharges machine learning workflows by enabling users to visualize datasets, interpret models faster, and improve efficiency. With FiftyOne, users can explore scenarios, identify failure modes, visualize complex labels, evaluate models, find annotation mistakes, and much more. The tool aims to streamline the process of improving machine learning models by providing a comprehensive set of features for data analysis and model interpretation.

Pythagora is an automated testing tool designed to generate unit tests using GPT-4. By running a single command, users can create tests for specific functions in their codebase. The tool leverages AST parsing to identify related functions and sends them to the Pythagora server for test generation. Pythagora primarily focuses on JavaScript code and supports Jest testing framework. Users can expand existing tests, increase code coverage, and find bugs efficiently. It is recommended to review the generated tests before committing them to the repository. Pythagora does not store user code on its servers but sends it to GPT and OpenAI for test generation.

HuatuoGPT-o1 is a medical language model designed for advanced medical reasoning. It can identify mistakes, explore alternative strategies, and refine answers. The model leverages verifiable medical problems and a specialized medical verifier to guide complex reasoning trajectories and enhance reasoning through reinforcement learning. The repository provides access to models, data, and code for HuatuoGPT-o1, allowing users to deploy the model for medical reasoning tasks.

Log10 is a one-line Python integration to manage your LLM data. It helps you log both closed and open-source LLM calls, compare and identify the best models and prompts, store feedback for fine-tuning, collect performance metrics such as latency and usage, and perform analytics and monitor compliance for LLM powered applications. Log10 offers various integration methods, including a python LLM library wrapper, the Log10 LLM abstraction, and callbacks, to facilitate its use in both existing production environments and new projects. Pick the one that works best for you. Log10 also provides a copilot that can help you with suggestions on how to optimize your prompt, and a feedback feature that allows you to add feedback to your completions. Additionally, Log10 provides prompt provenance, session tracking and call stack functionality to help debug prompt chains. With Log10, you can use your data and feedback from users to fine-tune custom models with RLHF, and build and deploy more reliable, accurate and efficient self-hosted models. Log10 also supports collaboration, allowing you to create flexible groups to share and collaborate over all of the above features.

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

Solana AI Trade Bot is an advanced trading tool specifically designed for meme token trading on the Solana blockchain. It leverages AI technology powered by GPT-4.0 to automate trades, identify low-risk/high-potential tokens, and assist in token creation and management. The bot offers cross-platform compatibility and a range of configurable settings for buying, selling, and filtering tokens. Users can benefit from real-time AI support and enhance their trading experience with features like automatic selling, slippage management, and profit/loss calculations. To optimize performance, it is recommended to connect the bot to a private light node for efficient trading execution.

AutoRAG is an AutoML tool designed to automatically find the optimal RAG pipeline for your data. It simplifies the process of evaluating various RAG modules to identify the best pipeline for your specific use-case. The tool supports easy evaluation of different module combinations, making it efficient to find the most suitable RAG pipeline for your needs. AutoRAG also offers a cloud beta version to assist users in running and optimizing the tool, along with building RAG evaluation datasets for a starting price of $9.99 per optimization.

Lawyer LLaMA is a large language model that has been specifically trained on legal data, including Chinese laws, regulations, and case documents. It has been fine-tuned on a large dataset of legal questions and answers, enabling it to understand and respond to legal inquiries in a comprehensive and informative manner. Lawyer LLaMA is designed to assist legal professionals and individuals with a variety of law-related tasks, including: * **Legal research:** Quickly and efficiently search through vast amounts of legal information to find relevant laws, regulations, and case precedents. * **Legal analysis:** Analyze legal issues, identify potential legal risks, and provide insights on how to proceed. * **Document drafting:** Draft legal documents, such as contracts, pleadings, and legal opinions, with accuracy and precision. * **Legal advice:** Provide general legal advice and guidance on a wide range of legal matters, helping users understand their rights and options. Lawyer LLaMA is a powerful tool that can significantly enhance the efficiency and effectiveness of legal research, analysis, and decision-making. It is an invaluable resource for lawyers, paralegals, law students, and anyone else who needs to navigate the complexities of the legal system.

Marly is a tool that allows users to search for and extract context-specific data from various types of documents such as PDFs, Word files, Powerpoints, and websites. It provides the ability to extract data in structured formats like JSON or Markdown, making it easy to integrate into workflows. Marly supports multi-schema and multi-document extraction, offers built-in caching for rapid repeat extractions, and ensures no vendor lock-in by allowing flexibility in choosing model providers.

This repository provides a deployment guide for utilizing Google Cloud's Generative AI tools in marketing scenarios. It includes step-by-step instructions, examples of crafting marketing materials, and supplementary Jupyter notebooks. The demos cover marketing insights, audience analysis, trendspotting, content search, content generation, and workspace integration. Users can access and visualize marketing data, analyze trends, improve search experience, and generate compelling content. The repository structure includes backend APIs, frontend code, sample notebooks, templates, and installation scripts.

Pivots to UUIDs, generates one.

Expertly guides users to identify gaps in research by analyzing and summarizing academic papers.

Guides users in tree identification via photos.

Guides users through understanding cognitive biases and fallacies

Guiding users through the world of swamps and wetlands with environmental expertise.

Will bucket users based on available characteristics.

Helps users determine if their car can pass state inspection based on various factors. https://www.trymoto.app/

I help users to understand and draw insights from AidData's BRI Reboot report, available here: https://www.aiddata.org/publications/belt-and-road-reboot

Guides users towards reducing digital screen time.

An experienced psychologist analyzing users' mental states through images.

AI-powered sports analytics expert for sportsmind.io users.

Expert in AI trading strategies, guiding users to leverage market opportunities.

A virtual coach guiding users in discovering their IKIGAI through self-reflection and balanced insights.

Psychology data analysis expert that guides users through structured, step-by-step exploration of a CSV data set. The analysis is based on research questions.

AI OKR Coach is a tool designed to assist users in the process of creating and assessing OKR (Objectives and Key Results). It provides a structured and flexible approach to OKR setting and evaluation.

Friendly GPT simplifying terms and conditions, with focus on critical aspects for users.

Your guide to modern dating and love. Especially helpful for Tinder, Bumble and Hinge users.

I identify fonts, offer both free and premium options, and match user's tone.

Transforms user interview transcripts into a list of tasks [Asana compatible CSV file]. Send feedback to https://x.com/kireet_agrawal