Best Artificial Intelligence Software for Kubernetes - Page 3
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Compare the Top Artificial Intelligence Software that integrates with Kubernetes as of November 2025 - Page 3
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This a list of Artificial Intelligence software that integrates with Kubernetes. Use the filters on the left to add additional filters for products that have integrations with Kubernetes. View the products that work with Kubernetes in the table below.
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1
Blue Hexagon
Blue Hexagon
We’ve designed our real-time deep learning platform to deliver speed of detection, efficacy and coverage that sets a new standard for cyber defense. We train our neural networks with global threat data that we’ve curated carefully via threat repositories, dark web, our deployments and from partners. Just like layers of neural networks can recognize your image in photos, our proprietary architecture of neural networks can identify threats in both payloads and headers. Every day, Blue Hexagon Labs validates the accuracy of our models with new threats in the wild. Our neural networks can identify a wide range of threats — file and fileless malware, exploits, C2 communications, malicious domains across Windows, Android, Linux platforms. Deep learning is a subset of machine learning that uses multi-layered artificial neural networks to learn data representation. -
2
Iterative
Iterative
AI teams face challenges that require new technologies. We build these technologies. Existing data warehouses and data lakes do not fit unstructured datasets like text, images, and videos. AI hand in hand with software development. Built with data scientists, ML engineers, and data engineers in mind. Don’t reinvent the wheel! Fast and cost‑efficient path to production. Your data is always stored by you. Your models are trained on your machines. Existing data warehouses and data lakes do not fit unstructured datasets like text, images, and videos. AI teams face challenges that require new technologies. We build these technologies. Studio is an extension of GitHub, GitLab or BitBucket. Sign up for the online SaaS version or contact us to get on-premise installation -
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Intel Tiber AI Studio
Intel
Intel® Tiber™ AI Studio is a comprehensive machine learning operating system that unifies and simplifies the AI development process. The platform supports a wide range of AI workloads, providing a hybrid and multi-cloud infrastructure that accelerates ML pipeline development, model training, and deployment. With its native Kubernetes orchestration and meta-scheduler, Tiber™ AI Studio offers complete flexibility in managing on-prem and cloud resources. Its scalable MLOps solution enables data scientists to easily experiment, collaborate, and automate their ML workflows while ensuring efficient and cost-effective utilization of resources. -
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Harness
Harness
Harness is an AI-native software delivery platform that helps engineering teams achieve excellence by automating and streamlining the entire software delivery lifecycle. It enables continuous integration, continuous delivery, and GitOps for multi-cloud, multi-region deployments with increased speed and reliability. Harness simplifies infrastructure as code, database DevOps, and artifact management to improve collaboration and reduce errors. The platform offers AI-powered testing, incident response, chaos engineering, and feature management to enhance quality and resilience. Harness also provides cloud cost management, security testing orchestration, and developer insights to optimize performance and governance. Trusted by leading enterprises, Harness accelerates innovation while reducing manual effort and risk. -
5
JFrog
JFrog
Fully automated DevOps platform for distributing trusted software releases from code to production. Onboard DevOps projects with users, resources and permissions for faster deployment frequency. Fearlessly update with proactive identification of open source vulnerabilities and license compliance violations. Achieve zero downtime across your DevOps pipeline with High Availability and active/active clustering for your enterprise. Control your DevOps environment with out-of-the-box native and ecosystem integrations. Enterprise ready with choice of on-prem, cloud, multi-cloud or hybrid deployments that scale as you grow. Ensure speed, reliability and security of IoT software updates and device management at scale. Create new DevOps projects in minutes and easily onboard team members, resources and storage quotas to get coding faster.Starting Price: $98 per month -
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DoiT
DoiT
DoiT is a global technology company that delivers a comprehensive cloud operations platform powered by proactive, industry-defining expertise so you can increase your operating margins and fuel innovation. DoiT Cloud Intelligence is the only context-aware multicloud intelligence platform that enables you to optimize, scale, and innovate. You turn insights into actions hand-in-hand with our cloud architects to make their cloud performant, reliable, and secure. An award-winning strategic partner of AWS, Google Cloud, and Microsoft Azure, we bring specializations in Kubernetes, GenAI, CloudOps, and more, to help more than 4,000 customers worldwide leverage the cloud to drive business growth and innovation.Starting Price: $0 -
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Launchable
Launchable
You can have the best developers in the world, but every test is making them slower. 80% of your software tests are pointless. The problem is you don't know which 80%. We find the right 20% using your data so that you can ship faster. We have shrink-wrapped predictive test selection, a machine learning-based approach being used at companies like Facebook so that it can be used by any company. We support multiple languages, test runners, and CI systems. Just bring Git to the table. Launchable uses machine learning to analyze your test failures and source code. It doesn't rely on code syntax analysis. This means it's trivial for Launchable to add support for almost any file-based programming language. It also means we can scale across teams and projects with different languages and tools. Out of the box, we currently support Python, Ruby, Java, JavaScript, Go, C, and C++, and we regularly add support for new languages. -
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Distributed AI is a computing paradigm that bypasses the need to move vast amounts of data and provides the ability to analyze data at the source. Distributed AI APIs built by IBM Research is a set of RESTful web services with data and AI algorithms to support AI applications across hybrid cloud, distributed, and edge computing environments. Each Distributed AI API addresses the challenges in enabling AI in distributed and edge environments with APIs. The Distributed AI APIs do not focus on the basic requirements of creating and deploying AI pipelines, for example, model training and model serving. You would use your favorite open-source packages such as TensorFlow or PyTorch. Then, you can containerize your application, including the AI pipeline, and deploy these containers at the distributed locations. In many cases, it’s useful to use a container orchestrator such as Kubernetes or OpenShift operators to automate the deployment process.
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9
Label Studio
Label Studio
The most flexible data annotation tool. Quickly installable. Build custom UIs or use pre-built labeling templates. Configurable layouts and templates adapt to your dataset and workflow. Detect objects on images, boxes, polygons, circular, and key points supported. Partition the image into multiple segments. Use ML models to pre-label and optimize the process. Webhooks, Python SDK, and API allow you to authenticate, create projects, import tasks, manage model predictions, and more. Save time by using predictions to assist your labeling process with ML backend integration. Connect to cloud object storage and label data there directly with S3 and GCP. Prepare and manage your dataset in our Data Manager using advanced filters. Support multiple projects, use cases, and data types in one platform. Start typing in the config, and you can quickly preview the labeling interface. At the bottom of the page, you have live serialization updates of what Label Studio expects as an input. -
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FluidStack
FluidStack
Unlock 3-5x better prices than traditional clouds. FluidStack aggregates under-utilized GPUs from data centers around the world to deliver the industry’s best economics. Deploy 50,000+ high-performance servers in seconds via a single platform and API. Access large-scale A100 and H100 clusters with InfiniBand in days. Train, fine-tune, and deploy LLMs on thousands of affordable GPUs in minutes with FluidStack. FluidStack unites individual data centers to overcome monopolistic GPU cloud pricing. Compute 5x faster while making the cloud efficient. Instantly access 47,000+ unused servers with tier 4 uptime and security from one simple interface. Train larger models, deploy Kubernetes clusters, render quicker, and stream with no latency. Setup in one click with custom images and APIs to deploy in seconds. 24/7 direct support via Slack, emails, or calls, our engineers are an extension of your team.Starting Price: $1.49 per month -
11
Cloud Cost Pro
Gathr.ai
Introducing Cloud Cost Pro, an industry-leading cloud cost optimization and FinOps solution. With Cloud Cost Pro, you get a 360-degree view of your multi-cloud environment, complete with actionable insights, ML-powered recommendations, and automated actions for streamlined cloud operations. Drive organization-wide improvements, enhance budgeting, and ensure compliance with security and resiliency best practices. Automate assessment of best practices and actions on budget violations and anomalies. Get ML-powered cost forecasts, anomaly detection, and optimization recommendations. Gain end-to-end, granular visibility into your cloud resources to ensure every dollar spent is accounted for. Track multi-cloud costs across different teams and business units easily. Get near real-time actionable insights to optimize cloud costs. With ML-powered anomaly detection, you can shut down any unauthorized, costly resource before costs snowball.Starting Price: Free -
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DagsHub
DagsHub
DagsHub is a collaborative platform designed for data scientists and machine learning engineers to manage and streamline their projects. It integrates code, data, experiments, and models into a unified environment, facilitating efficient project management and team collaboration. Key features include dataset management, experiment tracking, model registry, and data and model lineage, all accessible through a user-friendly interface. DagsHub supports seamless integration with popular MLOps tools, allowing users to leverage their existing workflows. By providing a centralized hub for all project components, DagsHub enhances transparency, reproducibility, and efficiency in machine learning development. DagsHub is a platform for AI and ML developers that lets you manage and collaborate on your data, models, and experiments, alongside your code. DagsHub was particularly designed for unstructured data for example text, images, audio, medical imaging, and binary files.Starting Price: $9 per month -
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Civo
Civo
Civo is a cloud-native platform designed to simplify cloud computing for developers and businesses, offering fast, predictable, and scalable infrastructure. It provides managed Kubernetes clusters with industry-leading launch times of around 90 seconds, enabling users to deploy and scale applications efficiently. Civo’s offering includes enterprise-class compute instances, managed databases, object storage, load balancers, and cloud GPUs powered by NVIDIA A100 for AI and machine learning workloads. Their billing model is transparent and usage-based, allowing customers to pay only for the resources they consume with no hidden fees. Civo also emphasizes sustainability with carbon-neutral GPU options. The platform is trusted by industry-leading companies and offers a robust developer experience through easy-to-use dashboards, APIs, and educational resources.Starting Price: $250 per month -
14
Chatwoot
Chatwoot
Chatwoot is a customer engagement suite that consolidates various communication channels, including email, website live chat, social media platforms like Facebook, Twitter, Instagram, and messaging apps such as WhatsApp and Line, into a unified dashboard. This integration enables businesses to deliver consistent customer experiences across multiple platforms. The platform offers features like canned responses for frequently asked questions, keyboard shortcuts for swift action execution, and team collaboration tools that allow internal discussions via private notes. Automation rules can be established to streamline repetitive tasks, and customizable live chat widgets can be added to websites to align with specific brand aesthetics. Chatwoot also supports chatbot integration and the embedding of custom dashboard applications, providing a comprehensive solution for managing customer interactions.Starting Price: $19 per month -
15
Axoflow
Axoflow
Detect and respond to threats faster, use AI, and reduce compliance breaches with the automatic Axoflow security data curation pipeline. Also reduces costs by 50% or more without coding, unless you really want to. The Axoflow Platform provides an end-to-end pipeline automating the collection, management, and ingestion of your security data in a vendor-agnostic way. The data transformation happens in the pipeline, resulting in data that is immediately actionable. No coding is needed at the destination, as it already arrives in a destination-optimized data model. Curation happens before it reaches the destination reducing data ingestion costs. The pipeline automatically identifies and classifies where the data is coming from. Enriches it with relevant context like geolocation if needed. Finally, converts it to a destination-optimized format. Remove infrastructure redundancy and consolidate data volume. -
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NVIDIA NIM
NVIDIA
Explore the latest optimized AI models, connect AI agents to data with NVIDIA NeMo, and deploy anywhere with NVIDIA NIM microservices. NVIDIA NIM is a set of easy-to-use inference microservices that facilitate the deployment of foundation models across any cloud or data center, ensuring data security and streamlined AI integration. Additionally, NVIDIA AI provides access to the Deep Learning Institute (DLI), offering technical training to gain in-demand skills, hands-on experience, and expert knowledge in AI, data science, and accelerated computing. AI models generate responses and outputs based on complex algorithms and machine learning techniques, and those responses or outputs may be inaccurate, harmful, biased, or indecent. By testing this model, you assume the risk of any harm caused by any response or output of the model. Please do not upload any confidential information or personal data unless expressly permitted. Your use is logged for security purposes. -
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Doctor Droid
Doctor Droid
Doctor Droid is an AI-driven platform designed to revolutionize monitoring and troubleshooting for engineering teams. It automates complex investigations, following standard operating procedures to analyze data across multiple integrations, identify root causes, and execute standard runbooks for self-healing. By proactively listening for alerts, Doctor Droid prepares relevant data and insights, reducing on-call time by up to 80% and enabling engineers to respond swiftly. It facilitates rapid onboarding of new engineers by automating the search for documents, learning new tools, and understanding data, allowing them to become primary on-calls from day one. With the capability to perform ad-hoc investigations, such as analyzing Kubernetes clusters or checking recent deployments, Doctor Droid adapts and creates new plans based on suggestions and existing documents. It integrates seamlessly with over 40 tools across the stack.Starting Price: $99 per month -
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Sesterce
Sesterce
Sesterce Cloud offers the seamless and simplest way to launch a GPU Cloud instance, in bare-metal or virtualized mode. Our platform is tailored to allow early-stage teams to collaborate, for training or deploying AI solutions through a large range of NVIDIA and AMD products and optimized pricing, in over 50 regions worldwide. We also offer packaged, turnkey AI solutions for companies that want to rapidly deploy tools to automate their processes, or develop new sources of growth. All with integrated customer support, 99.9% uptime, unlimited storage capacity.Starting Price: $0.30/GPU/hr -
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Skyportal
Skyportal
Skyportal is a GPU cloud platform built for AI engineers, offering 50% less cloud costs and 100% GPU performance. It provides a cost-effective GPU infrastructure for machine learning workloads, eliminating unpredictable cloud bills and hidden fees. Skyportal has seamlessly integrated Kubernetes, Slurm, PyTorch, TensorFlow, CUDA, cuDNN, and NVIDIA Drivers, fully optimized for Ubuntu 22.04 LTS and 24.04 LTS, allowing users to focus on innovating and scaling with ease. It offers high-performance NVIDIA H100 and H200 GPUs optimized specifically for ML/AI workloads, with instant scalability and 24/7 expert support from a team that understands ML workflows and optimization. Skyportal's transparent pricing and zero egress fees provide predictable costs for AI infrastructure. Users can share their AI/ML project requirements and goals, deploy models within the infrastructure using familiar tools and frameworks, and scale their infrastructure as needed.Starting Price: $2.40 per hour -
20
NetWatch.ai
NetWatch.ai
NetWatch.ai offers a comprehensive, AI-driven monitoring and security platform designed to replace fragmented tools with an integrated solution for modern IT environments. The platform is structured around three core product lines, NetWatch OPS, a server and network monitoring solution providing real-time insights, proactive alerts and streamlined resource management; Secure OPS, a hybrid SIEM built for unified security monitoring and compliance across cloud and on-premises infrastructures; and AI OPS, which uses machine learning to predict issues, automate remediation workflows and elevate operational performance. A patented “AI System Administrator” acts as a virtual operator that monitors customer infrastructure, connects via API to existing workflows, and offers complete visibility and automation. For organizations seeking turnkey expertise, NetWatch.ai also delivers Hive OPS SOC, a tiered Security Operations Center as a service with 24/7 monitoring, incident response, and more. -
21
Darktrace
Darktrace
Darktrace is a cybersecurity platform powered by AI, providing a proactive approach to cyber resilience. Its ActiveAI Security Platform delivers real-time threat detection, autonomous responses to both known and novel threats, and comprehensive visibility into an organization’s security posture. By ingesting enterprise data from native and third-party sources, Darktrace correlates security incidents across business operations and detects previously unseen threats. This complete visibility and automation reduce containment time, eliminate alert fatigue, and significantly enhance the efficiency of security operations. -
22
SOAtest
Parasoft
Anchored in artificial intelligence (AI) and machine learning (ML), Parasoft SOAtest simplifies the complexity of functional testing across APIs, UIs, databases, and more. Change management systems continuously monitor quality, making the API and web service testing tool a perfect fit for Agile DevOps environments. Parasoft SOAtest delivers fully integrated API and web service testing tools that automate end-to-end functional API testing. Streamline automated testing with advanced functional test-creation capabilities for applications with multiple interfaces (REST & SOAP APIs, microservices, databases, and more). The tools reduce the risk of security breaches and performance outages by transforming functional testing artifacts into security and load equivalents. Such reuse, along with continuous monitoring of API for change, allows faster and more efficient testing. -
23
MLflow
MLflow
MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects. -
24
EVA.ai
EVA.ai
EVA.ai HR Tech Automation Platform successfully optimises enterprise processes by personalising the experiences of Talent, Recruiters and Leaders at scale. The fourth industrial revolution applied to talent acquisition, management & engagement. EVA’s automation-first ethos helps organisations scale by combining exponential technologies with user-driven solutions that reduce waste and frustration across the HCM lifecycle. Drive personalised candidate experience at scale with EVABot – your people’s conversational assistant. Increase hiring teams productivity using ‘outcome-based’ automation, machine learning. Ensure hiring managers make the best decisions based on real-time process visibility. Give your talent acquisition function all the effectiveness tools required to deliver impactful experiences for candidates, HR executives and hiring managers at every touch-point across the hiring funnel. -
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Deep learning frameworks such as TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have contributed to the popularity of deep learning by reducing the effort and skills needed to design, train, and use deep learning models. Fabric for Deep Learning (FfDL, pronounced “fiddle”) provides a consistent way to run these deep-learning frameworks as a service on Kubernetes. The FfDL platform uses a microservices architecture to reduce coupling between components, keep each component simple and as stateless as possible, isolate component failures, and allow each component to be developed, tested, deployed, scaled, and upgraded independently. Leveraging the power of Kubernetes, FfDL provides a scalable, resilient, and fault-tolerant deep-learning framework. The platform uses a distribution and orchestration layer that facilitates learning from a large amount of data in a reasonable amount of time across compute nodes.
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Disruptica
Disruptica
Providing next-generation solutions at the intersection of artificial intelligence and software development. AI and automation should be easy. That’s why we build micro apps for specific industry use cases, think end-use applications for fraud detection, risk analytics, sales forecasting. Take our application estimator to get a better idea of project costs. Monolithic architecture can be frustrating. That's why we’re all about front and back-end microservice applications for a more flexible, scalable, and modern approach. Did we mention our own open-source platform? As a result, we’re able to update, upgrade, or rewrite just parts of an application seamlessly, resulting in more secure and reliable software. Start developing applications and adding AI/automation through resilient architecture today! We not only develop solutions, but also provide technical strategic plans for businesses to know how to implement, review, or scale their AI initiative. -
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Kubeflow
Kubeflow
The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow. Kubeflow provides a custom TensorFlow training job operator that you can use to train your ML model. In particular, Kubeflow's job operator can handle distributed TensorFlow training jobs. Configure the training controller to use CPUs or GPUs and to suit various cluster sizes. Kubeflow includes services to create and manage interactive Jupyter notebooks. You can customize your notebook deployment and your compute resources to suit your data science needs. Experiment with your workflows locally, then deploy them to a cloud when you're ready. -
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Polyaxon
Polyaxon
A Platform for reproducible and scalable Machine Learning and Deep Learning applications. Learn more about the suite of features and products that underpin today's most innovative platform for managing data science workflows. Polyaxon provides an interactive workspace with notebooks, tensorboards, visualizations,and dashboards. Collaborate with the rest of your team, share and compare experiments and results. Reproducible results with a built-in version control for code and experiments. Deploy Polyaxon in the cloud, on-premises or in hybrid environments, including single laptop, container management platforms, or on Kubernetes. Spin up or down, add more nodes, add more GPUs, and expand storage. -
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CoreWeave
CoreWeave
CoreWeave is a cloud infrastructure provider specializing in GPU-based compute solutions tailored for AI workloads. The platform offers scalable, high-performance GPU clusters that optimize the training and inference of AI models, making it ideal for industries like machine learning, visual effects (VFX), and high-performance computing (HPC). CoreWeave provides flexible storage, networking, and managed services to support AI-driven businesses, with a focus on reliability, cost efficiency, and enterprise-grade security. The platform is used by AI labs, research organizations, and businesses to accelerate their AI innovations. -
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NVIDIA Riva Studio
NVIDIA
Use the browser with in-app prompts and a recording tool. A predefined set of phonetically balanced sentences is available to create a 30-minute dataset for training a TTS model to learn your unique voice. Make the model sound like you by choosing the range that best suits the pitch of your voice. The recommended typical voice pitch range setting for a human voice is already provided, along with a preprogrammed best recipe to customize the TTS model for your voice. Generate an API to integrate a customized TTS model into your application. Download a deployable package with a helm chart to run on any cloud or on-premises Kubernetes cluster. Then, automatically host your voice microservice with NVIDIA, or set it up with just one-line of code. Set up, customize, and deploy the Riva TTS model with intuitive no-code, end-to-end GUI workflows and no infrastructure configuration.
