Best Artificial Intelligence Software for Kubernetes - Page 4
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Compare the Top Artificial Intelligence Software that integrates with Kubernetes as of November 2025 - Page 4
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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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Outerbounds
Outerbounds
Design and develop data-intensive projects with human-friendly, open-source Metaflow. Run, scale, and deploy them reliably on the fully managed Outerbounds platform. One platform for all your ML and data science projects. Access data securely from your existing data warehouses. Compute with a cluster optimized for scale and cost. 24/7 managed orchestration for production workflows. Use results to power any application. Give your data scientists superpowers, approved by your engineers. Outerbounds Platform allows data scientists to develop rapidly, experiment at scale, and deploy to production confidently. All within the outer bounds of policies and processes defined by your engineers, running on your cloud account, fully managed by us. Security is in our DNA, not at the perimeter. The platform adapts to your policies and compliance requirements through multiple layers of security. Centralized auth, a strict permission boundary, and granular task execution roles. -
2
UBOS
UBOS
Everything you need to transform your ideas into AI apps in minutes. Anyone can create next-generation AI-powered apps in 10 minutes, from professional developers to business users, using our no-code/low-code platform. Seamlessly integrate APIs like ChatGPT, Dalle-2, and Codex from Open AI, and even use custom ML models. Build custom admin client and CRUD functionalities to effectively manage sales, inventory, contracts, and more. Create dynamic dashboards that transform data into actionable insights and fuel innovation for your business. Easily create a chatbot to improve customer support and create a true omnichannel experience with multiple integrations. An all-in-one cloud platform combines low-code/no-code tools with edge technologies to make your web application scalable, secure, and easy to manage. Transform your software development process with our no-code/low-code platform, perfect for both business users and professional developers alike. -
3
Selenic
Parasoft
Selenium tests are often unstable and difficult to maintain. Parasoft Selenic fixes common Selenium problems within your existing projects with no vendor lock. When your team is using Selenium to develop and test the UI for your software applications, you need confidence that your testing process is identifying real issues, creating meaningful and appropriate tests, and reducing test maintenance. While Selenium offers many benefits, you want to get more out of your UI testing while leveraging your current practice. Find the real UI issues and get quick feedback on test execution so you can deliver better software faster with Parasoft Selenic. Improve your existing library of Selenium web UI tests, or quickly create new ones, with a flexible Selenium companion that integrates seamlessly with your environment. Parasoft Selenic fixes common Selenium problems with AI-powered self-healing to minimize runtime failures, test impact analysis to dramatically reduce test execution time, etc. -
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Second State
Second State
Fast, lightweight, portable, rust-powered, and OpenAI compatible. We work with cloud providers, especially edge cloud/CDN compute providers, to support microservices for web apps. Use cases include AI inference, database access, CRM, ecommerce, workflow management, and server-side rendering. We work with streaming frameworks and databases to support embedded serverless functions for data filtering and analytics. The serverless functions could be database UDFs. They could also be embedded in data ingest or query result streams. Take full advantage of the GPUs, write once, and run anywhere. Get started with the Llama 2 series of models on your own device in 5 minutes. Retrieval-argumented generation (RAG) is a very popular approach to building AI agents with external knowledge bases. Create an HTTP microservice for image classification. It runs YOLO and Mediapipe models at native GPU speed. -
5
Blink
Blink Ops
Blink is an ROI force multiplier for security teams and business leaders looking to quickly and easily secure a wide variety of use cases. Get full visibility and coverage of alerts across your organization and security stack. Utilize automated flows to reduce noise and false positives in alerts. Scan for attacks and proactively identify insider threats and vulnerabilities. Create automated workflows that add relevant context, streamline communications, and reduce MTTR. Take action on alerts and improve your cloud security posture with no-code automation and generative AI. Shift-left access requests, streamline approvals flows, and unblock developers while keeping your applications secure. Continuously monitor your application for SOC2, ISO, GDPR, or other compliance checks and enforce controls. -
6
Docu Dig
Docu Dig
Docu Dig is your business solution for easy and secure content search and insights within your documents. Elevate your organization's document insights with a customized Docu Dig solution. Unlock your documents' potential with AI-powered smart search and insights, securely. Docu Dig uses cutting-edge AI technology to securely enhance document insights retrieval, boosting team productivity and improving access to information. At Docu Dig, your data security is paramount. We use advanced encryption to protect your documents both at rest and in transit, ensuring they are secure at all times. For highly sensitive data, we provide private, sandboxed AI models in the cloud or the option of on-premises physical servers, guaranteeing that your data never leaves your premises. Unlike traditional methods that depend on exact keyword matches, our AI understands the context behind your queries, providing accurate insights from your chosen documents. -
7
RTMaps
Intempora
RTMaps (Real-time multisensor applications) is a highly-optimized component-based development and execution middleware. Thanks to RTMaps, developers can design complex real-time systems and perception algorithms for their autonomous applications such as mobile robots, railway, defense but also ADAS and Highly automated driving. RTMaps is a versatile swiss-knife tool to develop and execute your application and offering multiple key benefits: ● Asynchronous data acquisition ● Optimized performance ● Synchronous recording and playback ● Comprehensive component libraries: over 600 I/O software components available ● Flexible algorithm development: Share and collaborate ● Multi-platform processing ● Cross-platform compatibility and scalable: from PC, Embedded targets, to the Cloud. ● Rapid prototyping and testing ● Integration with dSPACE tools ● Time and resource savings ● Limiting Development risks, errors and efforts. ● Certification ISO26262 ASIL-B: on demand -
8
ModelOp
ModelOp
ModelOp is the leading AI governance software that helps enterprises safeguard all AI initiatives, including generative AI, Large Language Models (LLMs), in-house, third-party vendors, embedded systems, etc., without stifling innovation. Corporate boards and C‑suites are demanding the rapid adoption of generative AI but face financial, regulatory, security, privacy, ethical, and brand risks. Global, federal, state, and local-level governments are moving quickly to implement AI regulations and oversight, forcing enterprises to urgently prepare for and comply with rules designed to prevent AI from going wrong. Connect with AI Governance experts to stay informed about market trends, regulations, news, research, opinions, and insights to help you balance the risks and rewards of enterprise AI. ModelOp Center keeps organizations safe and gives peace of mind to all stakeholders. Streamline reporting, monitoring, and compliance adherence across the enterprise. -
9
StackGen
StackGen
Generate context-aware, secure IaC from application code without code changes. We love infrastructure as code, but that doesn’t mean there isn’t room for improvement. StackGen uses an application’s code to generate consistent, secure, and compliant IaC. Remove bottlenecks, liabilities, and error-prone manual processes between DevOps, developers, and security to get your application to market faster. Allow developers a better, more productive experience without becoming infrastructure experts. Consistency, security, and policy guardrails are incorporated by default when IaC is auto-generated. Context-aware IaC is auto-generated, with no code changes required, supported, and rightsized with least-privileged access controls. No need to rebuild your pipelines. StackGen works alongside your existing workflows to remove silos between teams. Enable developers to auto-generate IaC that complies with your provisioning checklist. -
10
Operant
Operant AI
Operant AI shields every layer of modern applications, from Infra to APIs. Within minutes of a single-step deployment, Operant provides full-stack security visibility and runtime controls, blocking a wide range of common and critical attacks including data exfiltration, data poisoning, zero day vulns, lateral movement, cryptomining, prompt injection, and more. All with zero instrumentation, zero drift, and zero friction between Dev, Sec, and Ops. Operant's in-line runtime protection of all data-in-use, across every interaction from infra to APIs, brings a new level of defense to your cloud-native apps with zero instrumentation, zero application code changes and zero integrations. -
11
Edera
Edera
Introducing secure-by-design AI and Kubernetes no matter where you run your infrastructure. Eliminate container escapes and put a security boundary around Kubernetes workloads. Simplify running AI/ML workloads through enhanced GPU device virtualization, driver isolation, and vGPUs. Edera Krata begins a new paradigm of isolation technology, ushering in a new era of security. Edera brings a new era of AI & GPU security and performance, while also integrating seamlessly with Kubernetes. Each container receives its own Linux kernel, eliminating a shared kernel state between containers. Which means goodbye container escapes, costly security tool layering, and long days doom scrolling logs. Run Edera Protect with just a couple lines of YAML and you’re off to the races. It’s written in Rust for enhanced memory safety and has no performance impact. A secure-by-design Kubernetes solution that stops attackers in their tracks. -
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Stratio
Stratio
A unified secure business data layer providing instant answers for business and data teams. Stratio generative AI data fabric covers the whole lifecycle of data management from data discovery, and governance, to use and disposal. Your organization has data all over the place, different divisions use different apps to do different things. Stratio uses AI to find all your data, whether it's on-prem or in the cloud. That means you can be sure that you're treating data appropriately. If you can't see your data as soon as its generated, you´ll never move as fast as your customers. With most data infrastructure, it can take hours to process customer data. Stratio accesses 100% of your data in real-time without moving it, so you can act quickly without losing the all-important context. Only by unifying the operational and informational in a collaborative platform companies will be able to move to instant extended AI. -
13
Simplismart
Simplismart
Fine-tune and deploy AI models with Simplismart's fastest inference engine. Integrate with AWS/Azure/GCP and many more cloud providers for simple, scalable, cost-effective deployment. Import open source models from popular online repositories or deploy your own custom model. Leverage your own cloud resources or let Simplismart host your model. With Simplismart, you can go far beyond AI model deployment. You can train, deploy, and observe any ML model and realize increased inference speeds at lower costs. Import any dataset and fine-tune open-source or custom models rapidly. Run multiple training experiments in parallel efficiently to speed up your workflow. Deploy any model on our endpoints or your own VPC/premise and see greater performance at lower costs. Streamlined and intuitive deployment is now a reality. Monitor GPU utilization and all your node clusters in one dashboard. Detect any resource constraints and model inefficiencies on the go. -
14
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. -
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Nutanix Enterprise AI
Nutanix
Make enterprise AI apps and data easy to deploy, operate, and develop with secure AI endpoints using AI large language models and APIs for generative AI. Nutanix Enterprise AI simplifies and secures GenAI, empowering enterprises to pursue unprecedented productivity gains, revenue growth, and the value that GenAI promises. Streamline workflows to help monitor and manage AI endpoints conveniently, unleashing your inner AI talent. Deploy AI models and secure APIs effortlessly with a point-and-click interface. Choose from Hugging Face, NVIDIA NIM, or your own private models. Run enterprise AI securely, on-premises, or in public clouds on any CNCF-certified Kubernetes runtime while leveraging your current AI tools. Easily create or remove access to your LLMs with role-based access controls of secure API tokens for developers and GenAI application owners. Create URL-ready JSON code for API-ready testing in a single click. -
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Pipeshift
Pipeshift
Pipeshift is a modular orchestration platform designed to facilitate the building, deployment, and scaling of open source AI components, including embeddings, vector databases, large language models, vision models, and audio models, across any cloud environment or on-premises infrastructure. The platform offers end-to-end orchestration, ensuring seamless integration and management of AI workloads, and is 100% cloud-agnostic, providing flexibility in deployment. With enterprise-grade security, Pipeshift addresses the needs of DevOps and MLOps teams aiming to establish production pipelines in-house, moving beyond experimental API providers that may lack privacy considerations. Key features include an enterprise MLOps console for managing various AI workloads such as fine-tuning, distillation, and deployment; multi-cloud orchestration with built-in auto-scalers, load balancers, and schedulers for AI models; and Kubernetes cluster management. -
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Token Security
Token Security
Token Security accelerates secure enterprise adoption of Agentic AI by discovering, managing, and governing every AI agent and non-human identity across the organization. From continuous visibility to least-privilege enforcement and lifecycle management, Token Security provides complete control over AI and machine identities, eliminating blind spots, reducing risk, and ensuring compliance at scale. -
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O-mega
O-mega
O-mega is the world's first productivity platform for multi-agent teams, enabling businesses to build AI agents for autonomous work. These agents are designed to take action safely, knowing when and how to use tools to execute tasks under the right conditions. They collaborate effectively across processes, departments, roles, and authorization levels, all while being aware of organizational context, mission, guidelines, and industry standards. O-mega connects agents universally to any platform, API, browser, or legacy system, including Slack, GitHub, Dropbox, Google, Microsoft, AWS, Shopify, Salesforce, Stripe, WordPress, LinkedIn, Twitter, YouTube, Discord, Apple, WhatsApp, and more. This connectivity allows for the automation of any business process through agentic process automation, with AI agents capable of handling tasks such as publishing blogs and posts, processing invoices, onboarding new employees, and generating weekly financial reports. -
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Kubiya
Kubiya
Kubiya is an AI-powered internal developer platform that leverages conversational AI to streamline DevOps processes. By integrating with existing tools and platforms, Kubiya enables developers to interact with their systems using natural language, reducing the time-to-automation and enhancing productivity. The platform offers AI teammates capable of handling routine tasks such as managing Jira queues, provisioning infrastructure, and enforcing just-in-time cloud permissions, allowing engineering teams to focus on higher-value activities. Kubiya's agentic-native design ensures predictable and secure operations, with enterprise-grade security measures and compliance with organizational policies. The platform integrates seamlessly into communication workflows, supporting tools like Slack and Microsoft Teams, to provide a conversational interface for task delegation and automation. -
20
Open WebUI
Open WebUI
Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline. It supports various LLM runners like Ollama and OpenAI-compatible APIs, with a built-in inference engine for Retrieval Augmented Generation (RAG), making it a powerful AI deployment solution. Key features include effortless setup via Docker or Kubernetes, seamless integration with OpenAI-compatible APIs, granular permissions and user groups for enhanced security, responsive design across devices, and full Markdown and LaTeX support for enriched interactions. Additionally, Open WebUI offers a Progressive Web App (PWA) for mobile devices, providing offline access and a native app-like experience. The platform also includes a Model Builder, allowing users to create custom models from base Ollama models directly within the interface. With over 156,000 users, Open WebUI is a versatile solution for deploying and managing AI models in a secure, offline environment. -
21
VLLM
VLLM
VLLM is a high-performance library designed to facilitate efficient inference and serving of Large Language Models (LLMs). Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry. It offers state-of-the-art serving throughput by efficiently managing attention key and value memory through its PagedAttention mechanism. It supports continuous batching of incoming requests and utilizes optimized CUDA kernels, including integration with FlashAttention and FlashInfer, to enhance model execution speed. Additionally, vLLM provides quantization support for GPTQ, AWQ, INT4, INT8, and FP8, as well as speculative decoding capabilities. Users benefit from seamless integration with popular Hugging Face models, support for various decoding algorithms such as parallel sampling and beam search, and compatibility with NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs, and more. -
22
Crusoe
Crusoe
Crusoe provides a cloud infrastructure specifically designed for AI workloads, featuring state-of-the-art GPU technology and enterprise-grade data centers. The platform offers AI-optimized computing, featuring high-density racks and direct liquid-to-chip cooling for superior performance. Crusoe’s system ensures reliable and scalable AI solutions with automated node swapping, advanced monitoring, and a customer success team that supports businesses in deploying production AI workloads. Additionally, Crusoe prioritizes sustainability by sourcing clean, renewable energy, providing cost-effective services at competitive rates. -
23
MLlib
Apache Software Foundation
Apache Spark's MLlib is a scalable machine learning library that integrates seamlessly with Spark's APIs, supporting Java, Scala, Python, and R. It offers a comprehensive suite of algorithms and utilities, including classification, regression, clustering, collaborative filtering, and tools for constructing machine learning pipelines. MLlib's high-quality algorithms leverage Spark's iterative computation capabilities, delivering performance up to 100 times faster than traditional MapReduce implementations. It is designed to operate across diverse environments, running on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or in the cloud, and accessing various data sources such as HDFS, HBase, and local files. This flexibility makes MLlib a robust solution for scalable and efficient machine learning tasks within the Apache Spark ecosystem. -
24
Observo AI
Observo AI
Observo AI is an AI-native data pipeline platform designed to address the challenges of managing vast amounts of telemetry data in security and DevOps operations. By leveraging machine learning and agentic AI, Observo AI automates data optimization, enabling enterprises to process AI-generated data more efficiently, securely, and cost-effectively. It reduces data processing costs by over 50% and accelerates incident response times by more than 40%. Observo AI's features include intelligent data deduplication and compression, real-time anomaly detection, and dynamic data routing to appropriate storage or analysis tools. It also enriches data streams with contextual information to enhance threat detection accuracy while minimizing false positives. Observo AI offers a searchable cloud data lake for efficient data storage and retrieval. -
25
NVIDIA DeepStream SDK
NVIDIA
NVIDIA's DeepStream SDK is a comprehensive streaming analytics toolkit based on GStreamer, designed for AI-based multi-sensor processing, including video, audio, and image understanding. It enables developers to create stream-processing pipelines that incorporate neural networks and complex tasks like tracking, video encoding/decoding, and rendering, facilitating real-time analytics on various data types. DeepStream is integral to NVIDIA Metropolis, a platform for building end-to-end services that transform pixel and sensor data into actionable insights. The SDK offers a powerful and flexible environment suitable for a wide range of industries, supporting multiple programming options such as C/C++, Python, and Graph Composer's intuitive UI. It allows for real-time insights by understanding rich, multi-modal sensor data at the edge and supports managed AI services through deployment in cloud-native containers orchestrated with Kubernetes. -
26
Qualcomm AI Inference Suite
Qualcomm
The Qualcomm AI Inference Suite is a comprehensive software platform designed to streamline the deployment of AI models and applications across cloud and on-premises environments. It offers seamless one-click deployment, allowing users to easily integrate their own models, including generative AI, computer vision, and natural language processing, and build custom applications using common frameworks. The suite supports a wide range of AI use cases such as chatbots, AI agents, retrieval-augmented generation (RAG), summarization, image generation, real-time translation, transcription, and code development. Powered by Qualcomm Cloud AI accelerators, it ensures top performance and cost efficiency through embedded optimization techniques and state-of-the-art models. It is designed with high availability and strict data privacy in mind, ensuring that model inputs and outputs are not stored, thus providing enterprise-grade security. -
27
Cleric
Cleric
Cleric is an autonomous AI Site Reliability Engineer (SRE) designed to manage, optimize, and heal software infrastructure without human intervention. It operates as an AI teammate, capable of investigating and diagnosing production issues by integrating with existing tools like Kubernetes, Datadog, Prometheus, and Slack. Cleric autonomously investigates alerts, handling routine work so engineers can focus on development. It checks systems concurrently, surfacing findings in minutes instead of the hours it takes to investigate manually. Cleric reasons through problems it’s never seen before by forming hypotheses, running real queries with their tools, and only sharing findings when confident. It levels up with every investigation, learning from real outcomes to real incidents. By Day 30, Cleric can autonomously handle 20–30% of the time spent on-call, allowing your team to focus on fixes rather than repetitive alert triage. -
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FPT Cloud
FPT Cloud
FPT Cloud is a next‑generation cloud computing and AI platform that streamlines innovation by offering a robust, modular ecosystem of over 80 services, from compute, storage, database, networking, and security to AI development, backup, disaster recovery, and data analytics, built to international standards. Its offerings include scalable virtual servers with auto‑scaling and 99.99% uptime; GPU‑accelerated infrastructure tailored for AI/ML workloads; FPT AI Factory, a comprehensive AI lifecycle suite powered by NVIDIA supercomputing (including infrastructure, model pre‑training, fine‑tuning, model serving, AI notebooks, and data hubs); high‑performance object and block storage with S3 compatibility and encryption; Kubernetes Engine for managed container orchestration with cross‑cloud portability; managed database services across SQL and NoSQL engines; multi‑layered security with next‑gen firewalls and WAFs; centralized monitoring and activity logging. -
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Azure Confidential Computing
Microsoft
Azure Confidential Computing increases data privacy and security by protecting data while it’s being processed, rather than only when stored or in transit. It encrypts data in memory within hardware-based trusted execution environments, only allowing computation to proceed after the cloud platform verifies the environment. This approach helps prevent access by cloud providers, administrators, or other privileged users. It supports scenarios such as multi-party analytics, allowing different organisations to contribute encrypted datasets and perform joint machine learning without revealing underlying data to each other. Users retain full control of their data and code, specifying which hardware and software can access it, and can migrate existing workloads with familiar tools, SDKs, and cloud infrastructure. -
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Mondoo
Mondoo
Mondoo is a unified security and compliance platform designed to drastically reduce business-critical vulnerabilities by combining full-stack asset visibility, risk prioritization, and agentic remediation. It builds a complete inventory of every asset, cloud, on-premises, SaaS, endpoints, network devices, and developer pipelines, and continuously assesses configurations, exposures, and interdependencies. It then applies business context (such as asset criticality, exploitability, and policy deviation) to score and highlight the most urgent risks. Users can choose guided remediation (pre-tested code snippets and playbooks) or autonomous remediation via orchestration pipelines, with tracking, ticket creation, and verification built in. Mondoo supports ingestion of third-party findings, integrates with DevSecOps toolchains (CI/CD, IaC, container registries), and includes 300 + compliance frameworks and benchmark templates.
