Best AI tools for< Schedule An Appointment >

BookingBee.ai is an AI appointment scheduling software that offers a comprehensive solution for beauty and wellness businesses. It provides an AI receptionist that handles appointment scheduling, lead capture, client engagement, and multilingual support. The platform helps businesses streamline operations, minimize no-shows, communicate with clients via text, and gain insights through real-time analytics. BookingBee.ai empowers businesses to grow by automating front-desk duties, marketing across channels, and turning one-time clients into repeat customers.

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.

CalenAI is an AI-powered scheduling agent that uses human-like voice technology to qualify leads and schedule appointments. It is designed to sound and feel just like a human, making it easy for customers to interact with and schedule appointments. CalenAI also offers personalized onboarding to help businesses set up the agent for their specific needs.

My AI Front Desk is an AI-powered virtual receptionist software designed for small businesses to automate scheduling, answer customer inquiries, and handle phone calls 24/7. It offers features such as capturing calls and appointments, sending texts, scheduling appointments, and providing tailored responses based on the business's services. Users can easily build and customize their AI receptionist in minutes, benefiting from advanced analytics and integration options. The application aims to help businesses improve customer service, increase efficiency, and never miss a call again.

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.

ChatFast is a platform that allows businesses to create custom GPT chatbots using their own data. These chatbots can be used to answer customer questions, capture leads, and schedule appointments. ChatFast is easy to use and requires no coding. It is trusted by thousands of businesses and provides a range of powerful features, including the ability to train chatbots on multiple data sources, revise responses, capture leads, and create smart forms.

Adept is building a machine learning model that can interact with everything on your computer. It takes your goals, in plain language, and turns them into actions on the software you use every day. Adept is designed and trained specifically for taking actions on computers in response to your natural language commands. ACT-1 is Adept's first step towards a foundation model that can use every software tool, API, and website that exists.

Outplay is a sales engagement and automation platform that helps businesses automate their outreach, follow-ups, and lead management. It offers a range of features such as multi-channel outreach, sales automation, conversation intelligence, and seamless CRM integration. Outplay is designed for fast-scaling SMBs and is trusted by over 5000 sales teams worldwide.

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

Droxy is the ultimate AI chatbot builder, offering an all-in-one no-code chatbot tool that allows users to easily create personalized chatbots for various purposes. With features like website integration, conversation analytics, lead generation, white label solutions, and automatic bookings, Droxy empowers businesses, educators, content creators, and community managers to enhance engagement and streamline communication. The platform enables seamless integration of AI assistants, provides insights on user interactions, and simplifies the process of converting content into interactive chatbots. Droxy is a game-changer in the AI chatbot industry, offering practical applications and endless possibilities for users to leverage AI technology.

Bot MD is an AI clinical assistant application that provides instant hospital information search, automates patient monitoring and care, and integrates with a wide range of hospital systems. It is used by thousands of doctors and nurses worldwide to streamline workflows, improve patient care, and enhance communication. The AI chat assistant helps healthcare professionals access clinical information quickly and efficiently, saving time and improving patient outcomes.

PreCallAI is a revolutionary Generative AI-powered voice bot designed to proactively engage and empathetically interact with clients. It empowers businesses by providing seamless revenue generation on autopilot. The application addresses issues such as timely support for potential customers, providing pertinent details to leads, sustaining continuous interaction, and plugging leaks in low-converting sales pipelines. PreCallAI offers features like elevating sales game, product education & discovery, lead qualification, lead nurturing, appointment scheduling/meetings, and demand generation.

CallBud is an AI tool designed to assist users in making appointment calls. It serves as a virtual assistant that can handle the task of scheduling appointments over the phone. With CallBud, users can save time and effort by automating the process of making calls and managing their appointments efficiently. The tool is user-friendly and provides a convenient solution for individuals who need assistance with their call-related tasks.

SimpleTalk AI is an advanced AI application that offers voice AI technology to businesses, enabling them to streamline customer interactions, automate tasks, and enhance communication efficiency. With features like universal calendar syncing, conversational AI voicemail replacement, seamless handoff capability, intelligent real-time interaction, and global communication capabilities, SimpleTalk AI revolutionizes customer relationship management. The application provides custom-made voice AI agents for various industries, such as real estate, solar, health insurance, tech support, and credit repair, offering tailored solutions for different use cases. SimpleTalk AI empowers businesses to break language barriers, automate for efficiency, innovate customer service, and maximize savings by leveraging AI-driven communication solutions.

TalkForce AI is an AI-powered customer care solution that revolutionizes customer service and operational efficiency. It offers 24/7 support, automated tasks, and personalized experiences to enhance customer satisfaction. The application integrates seamlessly with existing systems, providing tailored responses and efficient solutions for businesses across various industries.

Autocalls.ai is an AI-powered solution that automates business phone calls using artificial intelligence. It offers a seamless, fast, and efficient way to handle customer support calls. The platform allows users to create and manage phone call campaigns, access call history and analysis, view detailed reports, and integrate with existing CRM and ERP systems. Autocalls.ai ensures precise and efficient call management, reduces human errors, improves customer satisfaction, and provides 24/7 availability. With features like natural voices, multilingual support, and sentiment analysis, it enhances communication experiences for customers. The tool is scalable, adapts to various business needs, and offers benefits such as process efficiency, cost reduction, and quick response times.

ConvoLinx is an AI-powered virtual receptionist that optimizes call handling, resolves inquiries, and drives cost-effective customer support. It offers features such as customizable interactions, continuous availability, call forwarding, appointment scheduling, and custom call flows. ConvoLinx seamlessly integrates into business processes, allowing for the collection of specific customer information and the provision of tailored solutions. Its unique customer call flows can be customized for any interaction, creating personalized call handlers to improve customer experience and drive satisfaction.

Zappr.AI is an AI-powered platform that offers advanced chatbots for businesses to engage, support, and convert customers without the need for coding. The platform streamlines customer inquiries, scheduling, lead capture, and offers tailored solutions for various industries. With features like 24/7 availability, fast resolutions, and support for multiple document formats, Zappr.AI aims to boost efficiency and customer satisfaction while cutting down on human resource costs. The platform also integrates with popular messaging apps and CRM systems, ensuring seamless communication and lead generation.

CallFluent AI is an AI-powered voice call software that enables businesses to create AI-powered voice call agents in just 60 seconds. It transforms missed calls into revenue by automating inbound and outbound calls with artificial intelligence-powered robots. The platform offers human-like voices, real-time call history, recordings, and transcriptions, 24/7 inbound and outbound automated call management, and over 30 neural AI voices replicating human emotions. CallFluent AI provides a cost-effective solution for sales and customer service, allowing businesses to handle calls efficiently and effectively.

HumanLayer is a Python toolkit designed to enable AI agents to interact with humans in tool-based and asynchronous workflows. By incorporating humans-in-the-loop, agentic tools can access more powerful and meaningful tasks. The toolkit provides features like requiring human approval for function calls, human as a tool for contacting humans, omni-channel contact capabilities, granular routing, and support for various LLMs and orchestration frameworks. HumanLayer aims to ensure human oversight of high-stakes function calls, making AI agents more reliable and safe in executing impactful tasks.

Tools4AI is a Java-based Agentic Framework for building AI agents to integrate with enterprise Java applications. It enables the conversion of natural language prompts into actionable behaviors, streamlining user interactions with complex systems. By leveraging AI capabilities, it enhances productivity and innovation across diverse applications. The framework allows for seamless integration of AI with various systems, such as customer service applications, to interpret user requests, trigger actions, and streamline workflows. Prompt prediction anticipates user actions based on input prompts, enhancing user experience by proactively suggesting relevant actions or services based on context.

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.

Linguflex is a project that aims to simulate engaging, authentic, human-like interaction with AI personalities. It offers voice-based conversation with custom characters, alongside an array of practical features such as controlling smart home devices, playing music, searching the internet, fetching emails, displaying current weather information and news, assisting in scheduling, and searching or generating images.

Postiz is an ultimate AI social media scheduling tool that offers everything you need to manage your social media posts, build an audience, capture leads, and grow your business. It allows you to schedule posts with AI features, measure work with analytics, collaborate with team members, and invite others to comment and schedule posts. The tech stack includes NX (Monorepo), NextJS (React), NestJS, Prisma, Redis, and Resend for email notifications.

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

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.

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.

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.

Olah is a self-hosted lightweight Huggingface mirror service that implements mirroring feature for Huggingface resources at file block level, enhancing download speeds and saving bandwidth. It offers cache control policies and allows administrators to configure accessible repositories. Users can install Olah with pip or from source, set up the mirror site, and download models and datasets using huggingface-cli. Olah provides additional configurations through a configuration file for basic setup and accessibility restrictions. Future work includes implementing an administrator and user system, OOS backend support, and mirror update schedule task. Olah is released under the MIT License.

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.

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.

Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.

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.

ALLCHAT is a Node.js backend and React MUI frontend for an application that interacts with the Gemini Pro 1.5 (and others), with history, image generating/recognition, PDF/Word/Excel upload, code run, model function calls and markdown support. It is a comprehensive tool that allows users to connect models to the world with Web Tools, run locally, deploy using Docker, configure Nginx, and monitor the application using a dockerized monitoring solution (Loki+Grafana).

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.

Tiny, one for all, all for one!

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

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

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.

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

Your universal assist-friend.

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

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