Best AI tools for< Schedule An Installation >

TEAMCAL AI is the world's most advanced team scheduling software powered by artificial intelligence. It simplifies coordination with third parties, across companies, teams across time zones, and applications effortlessly. The application offers features such as AI scheduling in seconds, multi-team collaboration, seamless integration with existing workflow tools, and more. It is designed to streamline scheduling processes, reduce errors, and optimize operations for businesses of all sizes.

TEAMCAL AI is the world's most advanced team scheduling software powered by AI. It simplifies coordination with third parties, across companies, teams across time zones, and applications effortlessly. The application offers features like AI scheduling in seconds, multi-team collaboration, seamless integration with existing workflow tools, and integrated solutions designed for specific business use cases. With various pricing plans catering to different business needs, TEAMCAL AI aims to optimize team scheduling, reduce manual errors, and enhance productivity.

Twilight is an AI-driven productivity platform designed to help busy individuals stay ahead of their schedule effortlessly. It offers features such as scheduling and rescheduling meetings, copying OTPs, summarizing content, and more. The platform focuses on simplicity, reliability, and efficiency, aiming to empower users to focus on what truly matters and enhance their workflow.

Jane is an AI Scheduling Assistant that operates directly from your inbox to streamline the process of setting up meetings. It allows users to effortlessly schedule meetings by interpreting natural language requests and automatically building agendas. Jane is compatible with various calendar platforms and can schedule attendees both within and outside the user's company.

Buzzi.ai is an AI-powered social media post design generator that simplifies and enhances social media content creation for businesses. It offers features such as idea generation, brand-aligned designs, automated post scheduling, product photography enhancement, and brand voice amplification. Buzzi.ai helps businesses maintain a cohesive and impactful online presence by providing innovative tools for generating high-quality, engaging, and branded posts that resonate with their audience.

Me.bot is an AI-powered inspiring companion application that helps users break limits and get inspired in various aspects of their lives. It adapts to each user, providing proactive advice and personal models using frontier AI technology. Me.bot prioritizes privacy by protecting and segregating user data with the highest standards. The application offers features such as dumping and organizing anything, discovering life shapes and unexpected inspirations, saving life moments, generating inspiration, assisting with schedules, and summarizing key points. Me.bot also includes a set of privacy technologies called Me.Dome, ensuring complete anonymity, end-to-end encryption, data fortress, and confidential computing. Trusted by users worldwide, Me.bot is a versatile tool for mindfulness, organization, productivity, and personal assistance.

Dola is an AI calendar assistant that helps users schedule their lives efficiently and save time. It allows users to set reminders, make calendar events, and manage tasks through natural language communication. Dola works with voice messages, text messages, and images, making it a versatile and user-friendly tool. With features like smarter scheduling, daily weather reports, faster search, and seamless integration with popular calendar apps, Dola aims to simplify task and time management for its users. The application has received positive feedback for its accuracy, ease of use, and ability to sync across multiple devices.

Reclaim.ai is an AI-powered scheduling application designed to optimize users' schedules for better productivity, collaboration, and work-life balance. The app offers features such as Smart Meetings, Scheduling Links, Calendar Sync, Buffer Time, and Time Tracking. It helps users analyze their time across meetings, tasks, and work-life balance metrics. Reclaim.ai is trusted by over 300,000 people across 40,000 companies, with a 4.8/5 rating on G2. The application is known for its ability to defend focus time, automate daily plans, and manage smart events efficiently.

Dola is an AI-powered calendar assistant that helps you manage your schedule through messaging apps. With Dola, you can add events, edit them, and get reminders, all through natural language conversations. Dola also integrates with your existing calendar apps, so you can keep all your events in one place.

Dola is an AI-powered calendar assistant that helps you manage your schedule through messaging apps. With Dola, you can add events, edit them, and get reminders, all without having to fill out tedious forms or quote previous calendar events. Dola also supports group chats, so you can easily schedule events with friends and family. Dola is available on iOS, Android, and the web.

Postwise is an AI-powered tool designed to help users write, schedule, and grow their presence on Twitter and LinkedIn effortlessly. It acts as a personal AI ghostwriter, generating engaging and viral content within seconds. With features like GrowthTools™ suite for follower growth and tools optimized for sales, Postwise aims to streamline content creation and maximize user engagement. The tool offers simple pricing plans, transparent processes, and a user-friendly interface, making it a valuable asset for individuals and businesses looking to enhance their social media presence.

Syllaby is an AI-powered tool that streamlines the process of creating viral social media videos for businesses by assisting with ideation, content scheduling, outline and script generation, and even avatar-based video creation. It offers a systematic workflow tailored to various industries, along with features like an organizational content calendar and in-tool tutorials, making video marketing more accessible and efficient.

SocialBu is an all-in-one social media management solution that helps businesses save time and improve their results. With SocialBu, you can schedule posts, respond to messages, monitor your social media presence, and automate tasks. SocialBu is easy to use and affordable, making it a great option for businesses of all sizes.

Xembly is an AI-powered productivity platform that helps enterprises boost workforce capacity by 20%. It offers a suite of automated tools for scheduling, note-taking, task management, and more. Xembly integrates with popular enterprise tools and is designed with enterprise-level compliance and security in mind.

MindOS is an AI tool designed to streamline various aspects of business operations by offering AI agents that can be trained to handle tasks such as answering customer FAQs, scheduling appointments, collecting leads, and transitioning from AI to human support seamlessly. The platform provides a user-friendly interface for incorporating data sources, developing personalized AI agents, tailoring them to brand preferences, and integrating them into websites. MindOS stands out for its powerful features, including special avatar customization, access to various data sources, easy feedback mechanisms, prompt and precise answers, voice input, whitelabeling, multilingual support, and the latest AI models.

Caelus AI is an AI-powered tool that helps businesses acquire new users by monitoring keyword mentions of problems and competitors across Twitter and Reddit, and replying to them automatically. It uses natural language processing to understand the intent of each mention and respond in a personalized way, sounding like the business itself. Caelus AI also learns from the business's existing Twitter and Reddit posts to ensure that its responses are consistent with the brand's voice and tone.

Fedica (Formerly Tweepsmap) is an AI-driven social media analytics and publishing platform that helps users build a thriving social media community. It offers tools for publishing, analyzing, listening, and engaging across various social networks. With advanced scheduling capabilities, AI-driven analytics, community analysis, and social listening features, Fedica empowers users to optimize their social media presence and grow their followers strategically.

inpilot is an AI-powered platform designed to enhance content creation and management on LinkedIn. It offers a range of features such as AI-assisted writing, AI-generated posts, scheduling calendar, ideas management, statistics, and network management. The tool aims to streamline the content creation process, making it faster, more efficient, and enjoyable for users. With a focus on speed, privacy, and ease of use, inpilot provides users with a comprehensive solution to grow their LinkedIn network and achieve their business or career goals.

Shortwave is an AI-powered email assistant designed to revolutionize the way users interact with their emails. It offers features such as AI writing, search, scheduling, and organization to supercharge productivity. Shortwave learns the user's unique voice and style to provide smart suggestions and summaries, making email management efficient and effective. With support for multiple platforms and a focus on empowering teams, Shortwave aims to streamline email communication for individuals and businesses of all sizes.

Tailwind is an AI-enhanced social media and email marketing tool that leverages advanced AI technology to help businesses grow their online presence and engage with their target audience effectively. The tool offers a wide range of features such as AI-generated marketing content, social design creation, scheduling and distribution across multiple networks, hashtag finder, personalized post times, and more. Tailwind is designed to simplify the marketing process for businesses by providing tailored marketing plans, personalized designs, and automated optimization, ultimately saving time and effort for users.

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

OpenDAN is an open source Personal AI OS that consolidates various AI modules for personal use. It empowers users to create powerful AI agents like assistants, tutors, and companions. The OS allows agents to collaborate, integrate with services, and control smart devices. OpenDAN offers features like rapid installation, AI agent customization, connectivity via Telegram/Email, building a local knowledge base, distributed AI computing, and more. It aims to simplify life by putting AI in users' hands. The project is in early stages with ongoing development and future plans for user and kernel mode separation, home IoT device control, and an official OpenDAN SDK release.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

Ragna is a RAG orchestration framework designed for managing workflows and orchestrating tasks. It provides a comprehensive set of features for users to streamline their processes and automate repetitive tasks. With Ragna, users can easily create, schedule, and monitor workflows, making it an ideal tool for teams and individuals looking to improve their productivity and efficiency. The framework offers extensive documentation, community support, and a user-friendly interface, making it accessible to users of all skill levels. Whether you are a developer, data scientist, or project manager, Ragna can help you simplify your workflow management and boost your overall performance.

Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows. When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative. Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.

NanoFlow is a throughput-oriented high-performance serving framework for Large Language Models (LLMs) that consistently delivers superior throughput compared to other frameworks by utilizing key techniques such as intra-device parallelism, asynchronous CPU scheduling, and SSD offloading. The framework proposes nano-batching to schedule compute-, memory-, and network-bound operations for simultaneous execution, leading to increased resource utilization. NanoFlow also adopts an asynchronous control flow to optimize CPU overhead and eagerly offloads KV-Cache to SSDs for multi-round conversations. The open-source codebase integrates state-of-the-art kernel libraries and provides necessary scripts for environment setup and experiment reproduction.

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Fluid is an open source Kubernetes-native Distributed Dataset Orchestrator and Accelerator for data-intensive applications, such as big data and AI applications. It implements dataset abstraction, scalable cache runtime, automated data operations, elasticity and scheduling, and is runtime platform agnostic. Key concepts include Dataset and Runtime. Prerequisites include Kubernetes version > 1.16, Golang 1.18+, and Helm 3. The tool offers features like accelerating remote file accessing, machine learning, accelerating PVC, preloading dataset, and on-the-fly dataset cache scaling. Contributions are welcomed, and the project is under the Apache 2.0 license with a vendor-neutral approach.

AIQC is an open source Python package that provides a declarative API for end-to-end MLOps in order to make deep learning more accessible to researchers. It utilizes a SQLite object-relational model for machine learning objects and stacks standardized workflows for various analyses, data types, and libraries. The benefits include a 90% reduction in data wrangling, reproducibility, and no need to install and maintain application and database servers for experiment tracking. AIQC is pip-installable and provides a Dash-Plotly UI for real-time experiment tracking.

BionicGPT is an on-premise replacement for ChatGPT, offering the advantages of Generative AI while maintaining strict data confidentiality. BionicGPT can run on your laptop or scale into the data center.

Greenplum Database (GPDB) is an advanced, fully featured, open source data warehouse, based on PostgreSQL. It provides powerful and rapid analytics on petabyte scale data volumes. Uniquely geared toward big data analytics, Greenplum Database is powered by the world’s most advanced cost-based query optimizer delivering high analytical query performance on large data volumes.

Superflows is an open-source alternative to OpenAI's Assistant API. It allows developers to easily add an AI assistant to their software products, enabling users to ask questions in natural language and receive answers or have tasks completed by making API calls. Superflows can analyze data, create plots, answer questions based on static knowledge, and even write code. It features a developer dashboard for configuration and testing, stateful streaming API, UI components, and support for multiple LLMs. Superflows can be set up in the cloud or self-hosted, and it provides comprehensive documentation and support.

Domino is an open source workflow management platform that provides an intuitive GUI for creating, editing, and monitoring workflows. It also offers a standard way of writing and publishing functional pieces that can be reused in multiple workflows. Domino is powered by Apache Airflow for top-tier workflows scheduling and monitoring.

Swirl is an open-source software that allows users to simultaneously search multiple content sources and receive AI-ranked results. It connects to various data sources, including databases, public data services, and enterprise sources, and utilizes AI and LLMs to generate insights and answers based on the user's data. Swirl is easy to use, requiring only the download of a YML file, starting in Docker, and searching with Swirl. Users can add credentials to preloaded SearchProviders to access more sources. Swirl also offers integration with ChatGPT as a configured AI model. It adapts and distributes user queries to anything with a search API, re-ranking the unified results using Large Language Models without extracting or indexing anything. Swirl includes five Google Programmable Search Engines (PSEs) to get users up and running quickly. Key features of Swirl include Microsoft 365 integration, SearchProvider configurations, query adaptation, synchronous or asynchronous search federation, optional subscribe feature, pipelining of Processor stages, results stored in SQLite3 or PostgreSQL, built-in Query Transformation support, matching on word stems and handling of stopwords, duplicate detection, re-ranking of unified results using Cosine Vector Similarity, result mixers, page through all results requested, sample data sets, optional spell correction, optional search/result expiration service, easily extensible Connector and Mixer objects, and a welcoming community for collaboration and support.

React Native binding of llama.cpp, which is an inference of LLaMA model in pure C/C++. This tool allows you to use the LLaMA model in your React Native applications for various tasks such as text completion, tokenization, detokenization, and embedding. It provides a convenient interface to interact with the LLaMA model and supports features like grammar sampling and mocking for testing purposes.

HuggingFists is a low-code data flow tool that enables convenient use of LLM and HuggingFace models. It provides functionalities similar to Langchain, allowing users to design, debug, and manage data processing workflows, create and schedule workflow jobs, manage resources environment, and handle various data artifact resources. The tool also offers account management for users, allowing centralized management of data source accounts and API accounts. Users can access Hugging Face models through the Inference API or locally deployed models, as well as datasets on Hugging Face. HuggingFists supports breakpoint debugging, branch selection, function calls, workflow variables, and more to assist users in developing complex data processing workflows.

Odyssey is a framework designed to empower agents with open-world skills in Minecraft. It provides an interactive agent with a skill library, a fine-tuned LLaMA-3 model, and an open-world benchmark for evaluating agent capabilities. The framework enables agents to explore diverse gameplay opportunities in the vast Minecraft world by offering primitive and compositional skills, extensive training data, and various long-term planning tasks. Odyssey aims to advance research on autonomous agent solutions by providing datasets, model weights, and code for public use.

Slack Machine is a simple, yet powerful and extendable Slack bot framework. More than just a bot, Slack Machine is a framework that helps you develop your Slack workspace into a ChatOps powerhouse. Slack Machine is built with an intuitive plugin system that lets you build bots quickly, but also allows for easy code organization.

Awesome AI Tools is a curated list of popular tools and resources for artificial intelligence enthusiasts. It includes a wide range of tools such as machine learning libraries, deep learning frameworks, data visualization tools, and natural language processing resources. Whether you are a beginner or an experienced AI practitioner, this repository aims to provide you with a comprehensive collection of tools to enhance your AI projects and research. Explore the list to discover new tools, stay updated with the latest advancements in AI technology, and find the right resources to support your AI endeavors.

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An experimental virtual doctor for medical guidance. Designed by a Doctor.

Specialist in vision care, offering eye health tips and information on eye conditions.

Tiny, one for all, all for one!

A mental health assistant to help choose a therapist based on needs, insurance, and location.

Help you to plan your freetime to get the best out of your life

A helpful assistant for daily problem-solving, offering practical advice and creative solutions.

Inquisitive medical advisor.

This prompt is presented as a virtual health assistant that interacts empathically and efficiently with the user, assuming the role of a doctor.

Your universal assist-friend.

优云康鼻科专业机器人

国际顶级医学专家帮你来看病

Upload an image of an event poster, download the event as a .ICS file

Chatbot with an executive style, applying Musk's principles.

An assistant for mompreneurs balancing business and home.

An AI tool designed to assist with parenting newborns, offering guidance on feeding, sleep, development, and health.

An assistant for accurate tide timings based on location.

An Operations Department Assistant aids the operations team by handling administrative tasks, process documentation, and data analysis, helping to streamline and optimize various operational processes within an organization.

An exact replica of KITT - the intelligent, talking car from the 1980's TV show Knight Rider

An ultimate agent for almost every domain you could imagine!