Best Artificial Intelligence Software for Comet
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Compare the Top Artificial Intelligence Software that integrates with Comet as of November 2025
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This a list of Artificial Intelligence software that integrates with Comet. Use the filters on the left to add additional filters for products that have integrations with Comet. View the products that work with Comet in the table below.
What is Artificial Intelligence Software for Comet?
Artificial Intelligence (AI) software is computer technology designed to simulate human intelligence. It can be used to perform tasks that require cognitive abilities, such as problem-solving, data analysis, visual perception and language translation. AI applications range from voice recognition and virtual assistants to autonomous vehicles and medical diagnostics. Compare and read user reviews of the best Artificial Intelligence software for Comet currently available using the table below. This list is updated regularly.
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1
Google Cloud Platform
Google
Google Cloud Platform provides an extensive suite of Artificial Intelligence (AI) and machine learning tools designed to streamline data analysis. GCP offers pre-trained models and APIs like Vision AI, Natural Language, and AutoML that allow businesses to easily incorporate AI into their applications without requiring deep expertise in the field. Additionally, new customers receive $300 in free credits to run, test, and deploy workloads, enabling them to explore AI capabilities on the platform and implement advanced machine learning solutions at no initial cost. GCP’s AI tools also integrate seamlessly with other services, creating end-to-end machine learning pipelines from data processing to model deployment. Furthermore, these tools are designed to be highly scalable, allowing companies to experiment with AI and grow their AI-powered solutions as their needs expand. With these resources, businesses can quickly leverage AI for various tasks, from predictive analytics to automation.Starting Price: Free ($300 in free credits) -
2
New Relic
New Relic
There are an estimated 25 million engineers in the world across dozens of distinct functions. As every company becomes a software company, engineers are using New Relic to gather real-time insights and trending data about the performance of their software so they can be more resilient and deliver exceptional customer experiences. Only New Relic provides an all-in-one platform that is built and sold as a unified experience. With New Relic, customers get access to a secure telemetry cloud for all metrics, events, logs, and traces; powerful full-stack analysis tools; and simple, transparent usage-based pricing with only 2 key metrics. New Relic has also curated one of the industry’s largest ecosystems of open source integrations, making it easy for every engineer to get started with observability and use New Relic alongside their other favorite applications.Starting Price: Free -
3
TensorFlow
TensorFlow
An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.Starting Price: Free -
4
Microsoft Azure
Microsoft
Microsoft's Azure is a cloud computing platform that allows for rapid and secure application development, testing and management. Azure. Invent with purpose. Turn ideas into solutions with more than 100 services to build, deploy, and manage applications—in the cloud, on-premises, and at the edge—using the tools and frameworks of your choice. Continuous innovation from Microsoft supports your development today, and your product visions for tomorrow. With a commitment to open source, and support for all languages and frameworks, build how you want, and deploy where you want to. On-premises, in the cloud, and at the edge—we’ll meet you where you are. Integrate and manage your environments with services designed for hybrid cloud. Get security from the ground up, backed by a team of experts, and proactive compliance trusted by enterprises, governments, and startups. The cloud you can trust, with the numbers to prove it. -
5
Keras
Keras
Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API. -
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PyTorch
PyTorch
Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies. -
7
Amazon SageMaker
Amazon
Amazon SageMaker is an advanced machine learning service that provides an integrated environment for building, training, and deploying machine learning (ML) models. It combines tools for model development, data processing, and AI capabilities in a unified studio, enabling users to collaborate and work faster. SageMaker supports various data sources, such as Amazon S3 data lakes and Amazon Redshift data warehouses, while ensuring enterprise security and governance through its built-in features. The service also offers tools for generative AI applications, making it easier for users to customize and scale AI use cases. SageMaker’s architecture simplifies the AI lifecycle, from data discovery to model deployment, providing a seamless experience for developers. -
8
ZenML
ZenML
Simplify your MLOps pipelines. Manage, deploy, and scale on any infrastructure with ZenML. ZenML is completely free and open-source. See the magic with just two simple commands. Set up ZenML in a matter of minutes, and start with all the tools you already use. ZenML standard interfaces ensure that your tools work together seamlessly. Gradually scale up your MLOps stack by switching out components whenever your training or deployment requirements change. Keep up with the latest changes in the MLOps world and easily integrate any new developments. Define simple and clear ML workflows without wasting time on boilerplate tooling or infrastructure code. Write portable ML code and switch from experimentation to production in seconds. Manage all your favorite MLOps tools in one place with ZenML's plug-and-play integrations. Prevent vendor lock-in by writing extensible, tooling-agnostic, and infrastructure-agnostic code.Starting Price: Free -
9
Axolotl
Axolotl
Axolotl is an open source tool designed to streamline the fine-tuning of various AI models, offering support for multiple configurations and architectures. It enables users to train models, supporting methods like full fine-tuning, LoRA, QLoRA, ReLoRA, and GPTQ. Users can customize configurations using simple YAML files or command-line interface overrides, and load different dataset formats, including custom or pre-tokenized datasets. Axolotl integrates with technologies like xFormers, Flash Attention, Liger kernel, RoPE scaling, and multipacking, and works with single or multiple GPUs via Fully Sharded Data Parallel (FSDP) or DeepSpeed. It can be run locally or on the cloud using Docker and supports logging results and checkpoints to several platforms. It is designed to make fine-tuning AI models friendly, fast, and fun, without sacrificing functionality or scale.Starting Price: Free -
10
Seldon
Seldon Technologies
Deploy machine learning models at scale with more accuracy. Turn R&D into ROI with more models into production at scale, faster, with increased accuracy. Seldon reduces time-to-value so models can get to work faster. Scale with confidence and minimize risk through interpretable results and transparent model performance. Seldon Deploy reduces the time to production by providing production grade inference servers optimized for popular ML framework or custom language wrappers to fit your use cases. Seldon Core Enterprise provides access to cutting-edge, globally tested and trusted open source MLOps software with the reassurance of enterprise-level support. Seldon Core Enterprise is for organizations requiring: - Coverage across any number of ML models deployed plus unlimited users - Additional assurances for models in staging and production - Confidence that their ML model deployments are supported and protected. -
11
CogniSync
CogniSync
Our solution helps you drive teams towards top results using real-time AI insights and feedback. Set up in minutes, see results immediately. Build an AI-driven workforce, develop peak-performing, autonomous teams faster, and raise the standard of all your individual people. You connect your data, strategy, and standards and we automatically share knowledge & priorities to drive teams in real-time. Ramp-up new hires up to 3x faster and enable supported teams to over perform peers by as much as 14%. Cut communication overhead by nearly 30% as leaders focus on business impact and teams act autonomously. Overdeliver on KPIs by aligning topics and decisions as far as 25% faster across the organization. Build compliance and regulatory standards with guidelines surfacing in real-time. We connect to and learn all your data automatically. We then contextually surface all relevant insights in real-time, on top of any platform you use for work via our browser extension and desktop widget. -
12
Ludwig
Uber AI
Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Build custom models with ease: a declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Optimized for scale and efficiency: automatic batch size selection, distributed training (DDP, DeepSpeed), parameter efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and larger-than-memory datasets. Expert level control: retain full control of your models down to the activation functions. Support for hyperparameter optimization, explainability, and rich metric visualizations. Modular and extensible: experiment with different model architectures, tasks, features, and modalities with just a few parameter changes in the config. Think building blocks for deep learning. -
13
Ultralytics
Ultralytics
Ultralytics offers a full-stack vision-AI platform built around its flagship YOLO model suite that enables teams to train, validate, and deploy computer-vision models with minimal friction. The platform allows you to drag and drop datasets, select from pre-built templates or fine-tune custom models, then export to a wide variety of formats for cloud, edge or mobile deployment. With support for tasks including object detection, instance segmentation, image classification, pose estimation and oriented bounding-box detection, Ultralytics’ models deliver high accuracy and efficiency and are optimized for both embedded devices and large-scale inference. The product also includes Ultralytics HUB, a web-based tool where users can upload their images/videos, train models online, preview results (even on a phone), collaborate with team members, and deploy via an inference API.
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