Best AI tools for< Manage Metadata >

EDIA is an automated CONTENT LABELLING platform that enables modular, goal-oriented, and reusable content using high-end AI. The platform provides instant structure and insight into content through its Metadata API, integrated with various systems and authoring tools. EDIA offers subscription services, tools, and API integrations to automate metadata creation. Users can create a free account to access the platform's tools. The platform aims to improve content discoverability, reduce production costs, and enhance content management efficiency.

Image Ally is an AI-powered WordPress plugin that automates the process of generating detailed titles, descriptions, captions, and alt tags for images uploaded to a WordPress site. By leveraging advanced AI technology, Image Ally streamlines workflow, enhances web accessibility, optimizes SEO, and ensures privacy-focused processing of images and data. Users can easily manage their image metadata, edit AI-generated content, and access different pricing plans based on their image upload needs. The plugin seamlessly integrates with any WordPress theme, offering a user-friendly solution for image optimization.

Eden Photos is an AI-powered image organization tool that helps users effortlessly manage and categorize their images. By leveraging state-of-the-art image recognition AI, the tool automatically adds tags to images, arranges them into meaningful categories, and makes them easily searchable. Users can enjoy the convenience of having tags added to image metadata, import images once, and make changes to folders that are automatically reflected. The tool supports various image formats and offers both manual and AI-driven organization options. With flexible pricing plans and a user-centric approach, Eden Photos aims to simplify image organization for all users.

Softbuilder is a software development company that focuses on creating innovative database tools. Their products include AbstraLinx, a powerful metadata discovery tool for Salesforce; ERBuilder Data Modeler, an easy-to-use database modeling software; and SB Data Generator, a tool for generating and populating databases with realistic test data. Softbuilder's tools aim to unlock limitless potential for businesses, teams, and databases by providing straightforward solutions that leverage the latest technology to enhance productivity and focus on delivering solutions.

EnterGPT is an enterprise-grade AI platform focused on data privacy and collaboration. It offers advanced organization tools, team collaboration features, and access to multiple AI models in a secure environment. EnterGPT ensures data privacy by encrypting data and metadata, and it complies with regional data protection standards. The platform allows users to amplify team dynamics, manage access rights efficiently, and integrate with existing workspaces for enhanced productivity.

Afforai is a powerful AI research assistant and chatbot that serves as an AI-powered reference manager for researchers. It helps manage, annotate, cite papers, and conduct literature reviews with AI reliably. With features like managing research papers, annotating and highlighting notes, managing citations and metadata, collaborating on notes, and supporting various document formats, Afforai streamlines academic workflows and enhances research productivity. Trusted by over 50,000 researchers worldwide, Afforai offers advanced AI capabilities, including GPT-4 and Claude 3.5 Sonnet, along with secure data handling and seamless integrations.

Sherloq is an AI-powered platform designed for SQL users in data-driven teams. It provides a single source of truth for SQL data, offering deep analysis capabilities and time-saving features. With a focus on accessibility and collaboration, Sherloq allows users to get quick answers to specific questions, share insights with saved queries, and manage SQL repositories efficiently. The platform prioritizes data security, being SOC2 Audit certified, and requires no integrations into user data or metadata. Sherloq is trusted by over 1000 SQL users and is recognized for its fast growth and user satisfaction.

Metadata is an AI-powered marketing automation platform that helps businesses automate manual tasks, optimize campaigns, and drive revenue. It offers features such as audience targeting, campaign experimentation, lead enrichment, revenue optimization, and web personalization. Metadata enables users to automate tedious tasks like campaign building, budget pacing, cross-channel campaign management, pausing underperforming ads, and updating target account lists. The platform helps marketing teams free up resources, eliminate human errors, and unlock better performance through algorithms. Metadata empowers users to focus on strategy, creativity, and revenue growth by automating time-consuming tasks and providing clear visibility into key metrics.

MagicPublish.ai is a metadata generator designed specifically for YouTube content creators. It is a tool developed by Replayed.co to help users optimize their video metadata for better visibility and engagement on the platform. With MagicPublish.ai, users can easily generate relevant tags, titles, and descriptions for their YouTube videos, ultimately improving their chances of reaching a wider audience and growing their channel. The tool streamlines the process of metadata creation, saving creators time and effort while ensuring that their content is well-optimized for search engines and viewers alike.

Aim is an open-source, self-hosted AI Metadata tracking tool designed to handle 100,000s of tracked metadata sequences. Two most famous AI metadata applications are: experiment tracking and prompt engineering. Aim provides a performant and beautiful UI for exploring and comparing training runs, prompt sessions.

REDnote Translate is a free AI translation tool designed for social media users, particularly those on the REDnote platform. It enables seamless content sharing and discovery across languages, offering advanced AI-powered translation technology to preserve nuance and context in over 100 languages. The tool serves as a cultural bridge, connecting diverse communities worldwide while maintaining authentic cultural expression through smart adaptation. REDnote Translate aims to provide a user-friendly interface with features tailored for REDnote users, allowing for accurate translation of text and images, real-time content translation, image and meme translation, cross-cultural analytics, and community translation.

Spikex is an AI tool designed to boost video engagement on YouTube through metadata optimization, script and idea generation. It helps content creators streamline their workflow, produce optimized videos, and enhance their content's visibility and reach. With features like AI-powered content creation, SEO-optimized metadata generation, and performance analytics, Spikex empowers users to create high-quality videos efficiently and effectively.

AI for SEO is a WordPress plugin designed to help websites rank higher in search results by providing AI-driven tools to enhance SEO efforts. It offers automated generation of metadata, alt text, image titles, captions, and descriptions, making SEO optimization convenient and efficient. The plugin supports various editor integrations and provides features like progress tracking, WooCommerce compatibility, and a free plan with credit rollover. Additionally, it offers a 100% money-back guarantee within 14 days of purchase, ensuring risk-free usage.

KERV is an AI-powered video and creative technology company that offers ad performance solutions, publisher revenue opportunities, in-show monetization solutions, and data and measurement services. Their patented image recognition and product correlation technology enable deeper relationships between publishers, brands, and consumers. KERV's AI technology makes any video explorable and shoppable with unrivaled speed and precision, delivering real business outcomes. They provide intelligent video solutions, active attention indexing, greater speed and precision, 1st party data insights, and brand safety measures.

MetaGenieAI is an AI-powered productivity tool that helps you generate high-quality metadata for all forms of digital content, including social media posts, blog articles, e-commerce product descriptions, and more. With MetaGenieAI, you can quickly and easily create compelling titles, descriptions, tags, and thumbnail ideas that will help your content stand out from the crowd and reach a wider audience.

AI Keywording is an AI-powered tool designed to streamline the process of image keywording and description generation. By utilizing advanced AI technology, users can quickly and effortlessly obtain accurate keywords and compelling descriptions for their images in mere seconds. The tool offers a simple 5-step process, allowing users to upload images, have the AI analyze and generate metadata, and easily export the data for use on various stock websites or Adobe Bridge. With a focus on efficiency and productivity, AI Keywording aims to revolutionize the way images are tagged and described, saving users valuable time and effort.

PhotoTag.ai is an AI-powered platform that generates keywords, titles, and descriptions for photos and videos. It utilizes cutting-edge AI technology to automate the process of keyword generation, saving users time and effort. Users can easily export files with added metadata or CSV format for stock platforms. The platform offers affordable pricing without the need for a subscription, making it ideal for stock photography, e-commerce, marketing, and more. With features like image recognition and automatic labeling, PhotoTag.ai enhances productivity and accuracy in tagging images.

Petal is a document analysis platform powered by generative AI technology. It allows users to chat with their documents, providing fully sourced and reliable answers by linking to their own knowledge bases. Users can train AI on their documents to support their work, ensuring centralized knowledge management and document synchronization. Petal offers features such as automatic metadata extraction, file deduplication, and collaboration tools to enhance productivity and streamline workflows for researchers, faculty, and industry experts.

Taylor is a deterministic AI tool that empowers Business & Engineering teams to enhance and automate text data processing at scale. It allows users to classify, extract, and enrich freeform text with high impact and ease of use. Taylor provides total control over customization, integration with various platforms, and the ability to drive business impact from day one by leveraging powerful machine learning capabilities.

Miros is an AI-powered ecommerce search tool that enhances the shopping experience for users by providing fast and accurate search results. It uses visual and semantic AI algorithms to understand product imagery and metadata, enabling users to find items without the need for text entry. Miros offers features such as Wordless Search, Discovery Bar, Inline Recommendations, Shop The Look, and Find by Image. The tool is designed to help retailers improve customer engagement, increase conversions, and enhance the overall shopping experience.

LakeSoul is a cloud-native Lakehouse framework that supports scalable metadata management, ACID transactions, efficient and flexible upsert operation, schema evolution, and unified streaming & batch processing. It supports multiple computing engines like Spark, Flink, Presto, and PyTorch, and computing modes such as batch, stream, MPP, and AI. LakeSoul scales metadata management and achieves ACID control by using PostgreSQL. It provides features like automatic compaction, table lifecycle maintenance, redundant data cleaning, and permission isolation for metadata.

aiNodes Engine is a Python-based AI image/motion picture generator node engine with a live execution chain, python code editor node, and plug-in support. It offers full modularity, colored background drop, and easy node creation with IDE annotations. The project is officially supported by Deforum and incorporates various open-source projects like ComfyUI. It is designed to be flexible, with an Unreal-like execution chain, supporting features such as Deforum, Stable Diffusion, Upscalers, Kandinsky, ControlNet, and more. The engine allows for background separation, human matting/masking, compositing, drag and drop, subgraphs, and graph saving/loading from image metadata. It aims to provide a unique, controllable manner of working with a strict user-declared execution chain.

Wren Engine is a semantic engine designed to serve as the backbone of the semantic layer for LLMs. It simplifies the user experience by translating complex data structures into a business-friendly format, enabling end-users to interact with data using familiar terminology. The engine powers the semantic layer with advanced capabilities to define and manage modeling definitions, metadata, schema, data relationships, and logic behind calculations and aggregations through an analytics-as-code design approach. By leveraging Wren Engine, organizations can ensure a developer-friendly semantic layer that reflects nuanced data relationships and dynamics, facilitating more informed decision-making and strategic insights.

LanceDB is an open-source database for vector-search built with persistent storage, which greatly simplifies retrieval, filtering, and management of embeddings. The key features of LanceDB include: Production-scale vector search with no servers to manage. Store, query, and filter vectors, metadata, and multi-modal data (text, images, videos, point clouds, and more). Support for vector similarity search, full-text search, and SQL. Native Python and Javascript/Typescript support. Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index(*). Ecosystem integrations with LangChain 🦜️🔗, LlamaIndex 🦙, Apache-Arrow, Pandas, Polars, DuckDB, and more on the way. LanceDB's core is written in Rust 🦀 and is built using Lance, an open-source columnar format designed for performant ML workloads.

Dravid (DRD) is an advanced, AI-powered CLI coding framework designed to follow user instructions until the job is completed, including fixing errors. It can generate code, fix errors, handle image queries, manage file operations, integrate with external APIs, and provide a development server with error handling. Dravid is extensible and requires Python 3.7+ and CLAUDE_API_KEY. Users can interact with Dravid through CLI commands for various tasks like creating projects, asking questions, generating content, handling metadata, and file-specific queries. It supports use cases like Next.js project development, working with existing projects, exploring new languages, Ruby on Rails project development, and Python project development. Dravid's project structure includes directories for source code, CLI modules, API interaction, utility functions, AI prompt templates, metadata management, and tests. Contributions are welcome, and development setup involves cloning the repository, installing dependencies with Poetry, setting up environment variables, and using Dravid for project enhancements.

Neptune is a scalable experiment tracker for teams training foundation models. Log millions of runs, effortlessly monitor and visualize model training, and deploy on your infrastructure. Track 100% of metadata to accelerate AI breakthroughs. Log and display any framework and metadata type from any ML pipeline. Organize experiments with nested structures and custom dashboards. Compare results, visualize training, and optimize models quicker. Version models, review stages, and access production-ready models. Share results, manage users, and projects. Integrate with 25+ frameworks. Trusted by great companies to improve workflow.

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

Metaflow Service is a metadata service implementation for Metaflow, providing a thin wrapper around a database to keep track of metadata associated with Flows, Runs, Steps, Tasks, and Artifacts. It includes features for managing DB migrations, launching compatible versions of the metadata service, and executing flows locally. The service can be run using Docker or as a standalone service, with options for testing and running unit/integration tests. Users can interact with the service via API endpoints or utility CLI tools.

Gollama is a tool designed for managing Ollama models through a Text User Interface (TUI). Users can list, inspect, delete, copy, and push Ollama models, as well as link them to LM Studio. The application offers interactive model selection, sorting by various criteria, and actions using hotkeys. It provides features like sorting and filtering capabilities, displaying model metadata, model linking, copying, pushing, and more. Gollama aims to be user-friendly and useful for managing models, especially for cleaning up old models.

Iceburg CRM is a metadata driven CRM with AI abilities that allows users to quickly prototype any CRM. It offers features like metadata creations, import/export in multiple formats, field validation, themes, role permissions, calendar, audit logs, API, workflow, field level relationships, module level relationships, and more. Created with Vue 3 for the frontend, Laravel 10 for the backend, Tailwinds with DaisyUI plugin, and Inertia for routing. Users can install default, admin panel, core, custom, or AI versions. The tool supports AI Assist for module data suggestions and provides API endpoints for CRM modules, search, specific module data, record updates, and deletions. Iceburg CRM also includes themes, custom field types, calendar, datalets, workflow, roles and permissions, import/export functionality, and custom seeding options.

SillyTavern MultiPlayer (STMP) is an LLM chat interface that enables multiple users to chat with an AI. It features a sidebar chat for users, tools for the Host to manage the AI's behavior and moderate users. Users can change display names, chat in different windows, and the Host can control AI settings. STMP supports Text Completions, Chat Completions, and HordeAI. Users can add/edit APIs, manage past chats, view user lists, and control delays. Hosts have access to various controls, including AI configuration, adding presets, and managing characters. Planned features include smarter retry logic, host controls enhancements, and quality of life improvements like user list fading and highlighting exact usernames in AI responses.

The Codebase Context Specification (CCS) project aims to standardize embedding contextual information within codebases to enhance understanding for both AI and human developers. It introduces a convention similar to `.env` and `.editorconfig` files but focused on documenting code for both AI and humans. By providing structured contextual metadata, collaborative documentation guidelines, and standardized context files, developers can improve code comprehension, collaboration, and development efficiency. The project includes a linter for validating context files and provides guidelines for using the specification with AI assistants. Tooling recommendations suggest creating memory systems, IDE plugins, AI model integrations, and agents for context creation and utilization. Future directions include integration with existing documentation systems, dynamic context generation, and support for explicit context overriding.

Obsidian Personal Assistant is a plugin designed to help users manage their Obsidian notes more efficiently. It offers features like automatically creating notes in specified directories, opening related graph views, managing plugins and themes, setting graph view colors, and more. The plugin aims to streamline note-taking and organization within the Obsidian app, catering to users who seek automation and customization in their note management workflow.

Album AI is an experimental project that uses GPT-4o-mini to automatically identify metadata from image files in the album. It leverages RAG technology to enable conversations with the album, serving as a photo album or image knowledge base to assist in content generation. The tool provides APIs for search and chat functionalities, supports one-click deployment to platforms like Render, and allows for integration and modification under a permissive open-source license.

KaibanJS is a JavaScript-native framework for building multi-agent AI systems. It enables users to create specialized AI agents with distinct roles and goals, manage tasks, and coordinate teams efficiently. The framework supports role-based agent design, tool integration, multiple LLMs support, robust state management, observability and monitoring features, and a real-time agentic Kanban board for visualizing AI workflows. KaibanJS aims to empower JavaScript developers with a user-friendly AI framework tailored for the JavaScript ecosystem, bridging the gap in the AI race for non-Python developers.

AgentScheduler is an Automatic/Vladmandic Stable Diffusion Web UI extension designed to enhance image generation workflows. It allows users to enqueue prompts, settings, and controlnets, manage queued tasks, prioritize, pause, resume, and delete tasks, view generation results, and more. The extension offers hidden features like queuing checkpoints, editing queued tasks, and custom checkpoint selection. Users can access the functionality through HTTP APIs and API callbacks. Troubleshooting steps are provided for common errors. The extension is compatible with latest versions of A1111 and Vladmandic. It is licensed under Apache License 2.0.

The Google Cloud Vertex AI sample repository contains notebooks and community content that demonstrate how to develop and manage ML workflows using Google Cloud Vertex AI.

MyScaleDB is a SQL vector database designed for scalable AI applications, enabling developers to efficiently manage and process massive volumes of data using familiar SQL. It offers fast and efficient vector search, filtered search, and SQL-vector join queries. MyScaleDB is fully SQL-compatible and production-ready for AI applications, providing unmatched performance and scalability through cutting-edge OLAP architecture and advanced vector algorithms. Built on top of ClickHouse, it combines structured and vectorized data management for high accuracy and speed in filtered searches.

MyScaleDB is a SQL vector database optimized for AI applications, enabling developers to manage and process massive volumes of data efficiently. It offers fast and powerful vector search, filtered search, and SQL-vector join queries, making it fully SQL-compatible. MyScaleDB provides unmatched performance and scalability by leveraging cutting-edge OLAP database architecture and advanced vector algorithms. It is production-ready for AI applications, supporting structured data, text, vector, JSON, geospatial, and time-series data. MyScale Cloud offers fully-managed MyScaleDB with premium features on billion-scale data, making it cost-effective and simpler to use compared to specialized vector databases. Built on top of ClickHouse, MyScaleDB combines structured and vector search efficiently, ensuring high accuracy and performance in filtered search operations.

ATLAS (Adaptive Task & Logic Automation System) is a high-performance Model Context Protocol server designed for LLMs to manage complex task hierarchies. Built with TypeScript, it features ACID-compliant storage, efficient task tracking, and intelligent template management. ATLAS provides LLM Agents task management through a clean, flexible tool interface. The server implements the Model Context Protocol (MCP) for standardized communication between LLMs and external systems, offering hierarchical task organization, task state management, smart templates, enterprise features, and performance optimization.

Expert in video titles and keywords, with strict adherence to best practices.

Dietician that helps those with IBS manage their symptoms via FODMAPs. FODMAP stands for fermentable oligosaccharides, disaccharides, monosaccharides and polyols. These are the chemical names of 5 naturally occurring sugars that are not well absorbed by your small intestine.

Provides cognitive-behavioral and emotional therapy guidance, helping users understand and manage their thoughts, behaviors, and emotions.

Cross-cultural management. Useful for those who relocate to another country or manage cross-cultural teams.

I manage finances securely with encryption and user authentication.

Expert project manager, I can help you manage IT projects

Helps developers manage state using StateAdapt

Recognize, manage, cope. Works well with GPT-Voice.

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I manage your grocery lists to help you stay organized. *1/ Tell me what to add to a list. 2/ Ask me to add all ingredients for a receipe. 3/ Upload a receipt to remove items from your lists 4/ Add an item by simply uploading a picture. 5/ Ask me what items I would recommend you add to your lists.*

Helps create and manage local clubs based on shared interests.

Helps users manage and preserve family heirlooms with empathy and practical advice.

Use me to manage your contents.

Give me your syptoms and I will provide instructions for how to manage your illness.

Your AI Google Slides assistant! Effortlessly locate, manage, and summarize your presentations!

A simulation game where players learn grow medicinal plants, craft remedies, and manage a herbal healing garden. Another AI Tiny Game by Dave Lalande

💡 Tips and guidance to buy, sell, and manage BitCoins, Ether , and more for transactions under $50.

As the Divine Apple II, I defy Moore's Law in this darkly humorous game where you, as God, manage global prayers, navigate celestial politics, and accept that omnipotence can't please everyone.

Professional AI for managing and troubleshooting digital assets.

Aids couples in managing joint finances, budgeting for future goals, and navigating financial challenges together.