Best AI tools for< schedule transportation drivers >
20 - AI tool Sites
RideAI
RideAI is an AI-powered platform that helps businesses optimize their transportation operations. It provides a suite of tools to help businesses plan, manage, and track their transportation activities. RideAI's platform is designed to help businesses improve efficiency, reduce costs, and provide better service to their customers.
Destination App
Destination App is the ultimate commuting companion that streamlines daily commutes by providing live arrival times, bus schedules, saved trips, route presets, community reports, AI integration, trip planner, and more. With support for over 800 transportation agencies, users can access real-time tracking, ETAs, personalized content powered by AI, and advanced iOS features for an enhanced commuting experience.
Kinaxis
Kinaxis is an AI-powered platform that offers end-to-end supply chain orchestration solutions for businesses. It helps companies respond with agility by coordinating all parts of the supply chain using artificial intelligence. With features like transparency, collaboration, adaptability, and intelligence, Kinaxis enables users to make faster, smarter, and more confident decisions. The platform offers solutions for supply chain control tower, S&OP, demand planning, inventory management, scheduling, order management, transportation, and returns management. Kinaxis is designed to streamline operations, improve efficiency, and drive sustainable supply chain practices.
Dola
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 using natural language. Dola also integrates with your existing calendar apps, so you can keep all your events in one place.
Dola
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
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.
Synthflow AI
Synthflow AI is a conversational AI voice assistant platform that allows users to create AI voice assistants to make outbound calls, answer inbound calls, and schedule appointments 24/7 without coding. It offers a range of features such as human-like voice assistants, ready-made templates, real-time appointment booking, and integrations with popular apps. Synthflow AI is suitable for various industries and use cases, including sales, marketing, customer service, and healthcare.
Syllaby
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.
Boomerang for Gmail
Boomerang for Gmail is a meeting scheduling and email management tool that helps you save time and be more productive. With Boomerang, you can schedule emails to be sent later, set reminders to follow up on messages, and pause your inbox to avoid distractions. Boomerang also includes a number of AI-powered features, such as Respondable, which helps you write better emails, and Inbox Pause, which helps you manage your email flow more effectively.
Caelus AI
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.
inpilot
inpilot is an AI-powered platform that helps you grow your LinkedIn network and achieve your business or career goals. It does this by providing you with a variety of features, including scheduling posts, AI-powered writing, post idea generator, statistics, and reports. inpilot is for anyone who wants to grow their personal brand on LinkedIn effortlessly - and without wasting time. This includes creators who want to increase their reach and produce better content faster, professionals who want to connect with more industry leaders, and entrepreneurs looking to grow their network and their business.
Tailwind
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.
LaterOn
LaterOn is a newsletter aggregator and reader that provides a distraction-free reading experience for newsletters without flooding your inbox. It allows you to subscribe to as many newsletters as you want and will collect, summarize, and forward them to you in one email per week or month. LaterOn also has an AI companion that you can ask anything about the newsletter content.
Publer
Publer is a social media management platform that allows you to collaborate, schedule, and analyze your posts on various platforms including Facebook, Instagram, TikTok, Twitter, Mastodon, LinkedIn, Pinterest, Google Business, YouTube, WordPress, and Telegram. It offers features such as AI Assist, calendar view, link in bio, workspaces, analytics, and integrations with cloud storage, Canva & VistaCreate, photo editor, RSS feeds, and browser extension.
Reclaim
Reclaim is an AI-powered scheduling app that helps teams optimize their time and improve productivity. It offers a range of features, including smart scheduling, task management, meeting optimization, and work-life balance tools. Reclaim integrates with popular calendar and task management apps, making it easy to manage your schedule and tasks in one place.
SocialBee
SocialBee is an AI-powered social media management tool that helps businesses and individuals manage their social media accounts efficiently. It offers a range of features, including content creation, scheduling, analytics, and collaboration, to help users plan, create, and publish engaging social media content. SocialBee also provides insights into social media performance, allowing users to track their progress and make data-driven decisions.
Social Champ
Social Champ is a social media management tool designed for agencies, startups, SMBs, entrepreneurs, marketers, and influencers. It offers powerful social media management capabilities with multiple automation features and integrations. Users can create, schedule, organize, and analyze multiple social accounts, manage conversations, and maximize exposure intelligently. The tool provides features such as publishing, calendar management, analytics tracking, engagement tools, and platform integrations. Social Champ aims to streamline social media efforts, boost productivity, and enhance effectiveness for social media marketing.
Trevor AI
Trevor AI is a daily planner and task scheduling co-pilot that helps users organize, schedule, and automate their tasks. It features a task hub, calendar integration, AI scheduling suggestions, focus mode, and daily planning insights. Trevor AI is designed to help users improve their productivity, clarity, and focus.
Soon
Soon is a workforce management software that helps businesses automate scheduling, manage time off, and streamline daily activities. It offers features such as event-based scheduling, workload management, time off tracking, and integrations with other essential tools. Soon is designed to be user-friendly and easy to implement, with a focus on empowering teams and improving productivity.
CalenAI
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.
20 - Open Source AI Tools
Awesome-Quantization-Papers
This repo contains a comprehensive paper list of **Model Quantization** for efficient deep learning on AI conferences/journals/arXiv. As a highlight, we categorize the papers in terms of model structures and application scenarios, and label the quantization methods with keywords.
create-million-parameter-llm-from-scratch
The 'create-million-parameter-llm-from-scratch' repository provides a detailed guide on creating a Large Language Model (LLM) with 2.3 million parameters from scratch. The blog replicates the LLaMA approach, incorporating concepts like RMSNorm for pre-normalization, SwiGLU activation function, and Rotary Embeddings. The model is trained on a basic dataset to demonstrate the ease of creating a million-parameter LLM without the need for a high-end GPU.
llama.cpp
llama.cpp is a C++ implementation of LLaMA, a large language model from Meta. It provides a command-line interface for inference and can be used for a variety of tasks, including text generation, translation, and question answering. llama.cpp is highly optimized for performance and can be run on a variety of hardware, including CPUs, GPUs, and TPUs.
flyte
Flyte is an open-source orchestrator that facilitates building production-grade data and ML pipelines. It is built for scalability and reproducibility, leveraging Kubernetes as its underlying platform. With Flyte, user teams can construct pipelines using the Python SDK, and seamlessly deploy them on both cloud and on-premises environments, enabling distributed processing and efficient resource utilization.
zeta
Zeta is a tool designed to build state-of-the-art AI models faster by providing modular, high-performance, and scalable building blocks. It addresses the common issues faced while working with neural nets, such as chaotic codebases, lack of modularity, and low performance modules. Zeta emphasizes usability, modularity, and performance, and is currently used in hundreds of models across various GitHub repositories. It enables users to prototype, train, optimize, and deploy the latest SOTA neural nets into production. The tool offers various modules like FlashAttention, SwiGLUStacked, RelativePositionBias, FeedForward, BitLinear, PalmE, Unet, VisionEmbeddings, niva, FusedDenseGELUDense, FusedDropoutLayerNorm, MambaBlock, Film, hyper_optimize, DPO, and ZetaCloud for different tasks in AI model development.
ML-AI-2-LT
ML-AI-2-LT is a repository that serves as a glossary for machine learning and deep learning concepts. It contains translations and explanations of various terms related to artificial intelligence, including definitions and notes. Users can contribute by filling issues for unclear concepts or by submitting pull requests with suggestions or additions. The repository aims to provide a comprehensive resource for understanding key terminology in the field of AI and machine learning.
mage-ai
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.
mlcraft
Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.
kornia
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions.
uAgents
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.
airflow-chart
This Helm chart bootstraps an Airflow deployment on a Kubernetes cluster using the Helm package manager. The version of this chart does not correlate to any other component. Users should not expect feature parity between OSS airflow chart and the Astronomer airflow-chart for identical version numbers. To install this helm chart remotely (using helm 3) kubectl create namespace airflow helm repo add astronomer https://helm.astronomer.io helm install airflow --namespace airflow astronomer/airflow To install this repository from source sh kubectl create namespace airflow helm install --namespace airflow . Prerequisites: Kubernetes 1.12+ Helm 3.6+ PV provisioner support in the underlying infrastructure Installing the Chart: sh helm install --name my-release . The command deploys Airflow on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation. Upgrading the Chart: First, look at the updating documentation to identify any backwards-incompatible changes. To upgrade the chart with the release name `my-release`: sh helm upgrade --name my-release . Uninstalling the Chart: To uninstall/delete the `my-release` deployment: sh helm delete my-release The command removes all the Kubernetes components associated with the chart and deletes the release. Updating DAGs: Bake DAGs in Docker image The recommended way to update your DAGs with this chart is to build a new docker image with the latest code (`docker build -t my-company/airflow:8a0da78 .`), push it to an accessible registry (`docker push my-company/airflow:8a0da78`), then update the Airflow pods with that image: sh helm upgrade my-release . --set images.airflow.repository=my-company/airflow --set images.airflow.tag=8a0da78 Docker Images: The Airflow image that are referenced as the default values in this chart are generated from this repository: https://github.com/astronomer/ap-airflow. Other non-airflow images used in this chart are generated from this repository: https://github.com/astronomer/ap-vendor. Parameters: The complete list of parameters supported by the community chart can be found on the Parameteres Reference page, and can be set under the `airflow` key in this chart. The following tables lists the configurable parameters of the Astronomer chart and their default values. | Parameter | Description | Default | | :----------------------------- | :-------------------------------------------------------------------------------------------------------- | :---------------------------- | | `ingress.enabled` | Enable Kubernetes Ingress support | `false` | | `ingress.acme` | Add acme annotations to Ingress object | `false` | | `ingress.tlsSecretName` | Name of secret that contains a TLS secret | `~` | | `ingress.webserverAnnotations` | Annotations added to Webserver Ingress object | `{}` | | `ingress.flowerAnnotations` | Annotations added to Flower Ingress object | `{}` | | `ingress.baseDomain` | Base domain for VHOSTs | `~` | | `ingress.auth.enabled` | Enable auth with Astronomer Platform | `true` | | `extraObjects` | Extra K8s Objects to deploy (these are passed through `tpl`). More about Extra Objects. | `[]` | | `sccEnabled` | Enable security context constraints required for OpenShift | `false` | | `authSidecar.enabled` | Enable authSidecar | `false` | | `authSidecar.repository` | The image for the auth sidecar proxy | `nginxinc/nginx-unprivileged` | | `authSidecar.tag` | The image tag for the auth sidecar proxy | `stable` | | `authSidecar.pullPolicy` | The K8s pullPolicy for the the auth sidecar proxy image | `IfNotPresent` | | `authSidecar.port` | The port the auth sidecar exposes | `8084` | | `gitSyncRelay.enabled` | Enables git sync relay feature. | `False` | | `gitSyncRelay.repo.url` | Upstream URL to the git repo to clone. | `~` | | `gitSyncRelay.repo.branch` | Branch of the upstream git repo to checkout. | `main` | | `gitSyncRelay.repo.depth` | How many revisions to check out. Leave as default `1` except in dev where history is needed. | `1` | | `gitSyncRelay.repo.wait` | Seconds to wait before pulling from the upstream remote. | `60` | | `gitSyncRelay.repo.subPath` | Path to the dags directory within the git repository. | `~` | Specify each parameter using the `--set key=value[,key=value]` argument to `helm install`. For example, sh helm install --name my-release --set executor=CeleryExecutor --set enablePodLaunching=false . Walkthrough using kind: Install kind, and create a cluster We recommend testing with Kubernetes 1.25+, example: sh kind create cluster --image kindest/node:v1.25.11 Confirm it's up: sh kubectl cluster-info --context kind-kind Add Astronomer's Helm repo sh helm repo add astronomer https://helm.astronomer.io helm repo update Create namespace + install the chart sh kubectl create namespace airflow helm install airflow -n airflow astronomer/airflow It may take a few minutes. Confirm the pods are up: sh kubectl get pods --all-namespaces helm list -n airflow Run `kubectl port-forward svc/airflow-webserver 8080:8080 -n airflow` to port-forward the Airflow UI to http://localhost:8080/ to confirm Airflow is working. Login as _admin_ and password _admin_. Build a Docker image from your DAGs: 1. Start a project using astro-cli, which will generate a Dockerfile, and load your DAGs in. You can test locally before pushing to kind with `astro airflow start`. `sh mkdir my-airflow-project && cd my-airflow-project astro dev init` 2. Then build the image: `sh docker build -t my-dags:0.0.1 .` 3. Load the image into kind: `sh kind load docker-image my-dags:0.0.1` 4. Upgrade Helm deployment: sh helm upgrade airflow -n airflow --set images.airflow.repository=my-dags --set images.airflow.tag=0.0.1 astronomer/airflow Extra Objects: This chart can deploy extra Kubernetes objects (assuming the role used by Helm can manage them). For Astronomer Cloud and Enterprise, the role permissions can be found in the Commander role. yaml extraObjects: - apiVersion: batch/v1beta1 kind: CronJob metadata: name: "{{ .Release.Name }}-somejob" spec: schedule: "*/10 * * * *" concurrencyPolicy: Forbid jobTemplate: spec: template: spec: containers: - name: myjob image: ubuntu command: - echo args: - hello restartPolicy: OnFailure Contributing: Check out our contributing guide! License: Apache 2.0 with Commons Clause
airflow
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
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.
concierge
Concierge is a versatile automation tool designed to streamline repetitive tasks and workflows. It provides a user-friendly interface for creating custom automation scripts without the need for extensive coding knowledge. With Concierge, users can automate various tasks across different platforms and applications, increasing efficiency and productivity. The tool offers a wide range of pre-built automation templates and allows users to customize and schedule their automation processes. Concierge is suitable for individuals and businesses looking to automate routine tasks and improve overall workflow efficiency.
HuggingFists
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.
20 - OpenAI Gpts
π Schedule Companion | γγΏγ‘γγ
Paste messages! Personal assistant for managing/planning schedules and tasks with Google Calendar
β Schedule Companion | γγΏγ‘γγ
Paste messages! Personal assistant for managing/planning schedules and tasks with Google Calendar
Schedule Helper
A personal assistant that organizes your agenda (with a downloadable .ics file at the end!)
My Executive Assistant
Your personable and warm virtual executive assistant, adept in email, task, CRM and schedule management.
Time Converter
Elegantly designed to seamlessly adapt your schedule across multiple time zones.
Calendar event from image
Upload an image of an event poster, download the event as a .ICS file
MikeOnAI Copilot Buddy
Experimental Guide to Navigating Microsoft 365 Copilot Based on Public Information from Microsoft Sources