Best Artificial Intelligence Software for Kubernetes - Page 2

Compare the Top Artificial Intelligence Software that integrates with Kubernetes as of November 2025 - Page 2

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.

  • 1
    Ona

    Ona

    Ona

    Ona, formerly Gitpod, is a modern development platform that provides mission control for software projects and engineering agents. It allows developers to keep momentum on any device by offering sandboxed, API-first environments in the cloud or within a company’s VPC. These environments come pre-configured with tools, dependencies, and controls, ensuring a consistent and secure setup for professional software engineering. Ona Agents further enhance productivity by assisting with tasks like scoping, writing, reviewing, and documenting code across the entire development lifecycle. Enterprise-ready guardrails deliver fine-grained permissions, policies, and audit trails, giving organizations full control over compliance and security. Trusted by millions of developers and Fortune 500 companies, Ona integrates seamlessly with tools like GitHub, GitLab, AWS, Copilot, and Amazon Bedrock.
    Starting Price: $20/month
  • 2
    Opsani

    Opsani

    Opsani

    We are the only solution on the market that autonomously tunes applications at scale, either for a single application or across the entire service delivery platform. Opsani rightsizes your application autonomously so your cloud application works harder and leaner so you don’t have to. Opsani COaaS maximizes cloud workload performance and efficiency using the latest in AI and Machine Learning to continuously reconfigure and tune with every code release, load profile change, and infrastructure upgrade. We accomplish this while integrating easily with either a single app or across your service delivery platform while also scaling autonomously across 1000’s of services. Opsani allows for you to solve for all three autonomously without compromise. Reduce costs up to 71% by leveraging Opsani's AI algorithms. Opsani optimization continuously evaluates trillions of configuration permutations and pinpoints the best combinations of resources and parameter settings.
    Starting Price: $500 per month
  • 3
    Elastic Observability
    Rely on the most widely deployed observability platform available, built on the proven Elastic Stack (also known as the ELK Stack) to converge silos, delivering unified visibility and actionable insights. To effectively monitor and gain insights across your distributed systems, you need to have all your observability data in one stack. Break down silos by bringing together the application, infrastructure, and user data into a unified solution for end-to-end observability and alerting. Combine limitless telemetry data collection and search-powered problem resolution in a unified solution for optimal operational and business results. Converge data silos by ingesting all your telemetry data (metrics, logs, and traces) from any source in an open, extensible, and scalable platform. Accelerate problem resolution with automatic anomaly detection powered by machine learning and rich data analytics.
    Starting Price: $16 per month
  • 4
    KServe

    KServe

    KServe

    Highly scalable and standards-based model inference platform on Kubernetes for trusted AI. KServe is a standard model inference platform on Kubernetes, built for highly scalable use cases. Provides performant, standardized inference protocol across ML frameworks. Support modern serverless inference workload with autoscaling including a scale to zero on GPU. Provides high scalability, density packing, and intelligent routing using ModelMesh. Simple and pluggable production serving for production ML serving including prediction, pre/post-processing, monitoring, and explainability. Advanced deployments with the canary rollout, experiments, ensembles, and transformers. ModelMesh is designed for high-scale, high-density, and frequently-changing model use cases. ModelMesh intelligently loads and unloads AI models to and from memory to strike an intelligent trade-off between responsiveness to users and computational footprint.
    Starting Price: Free
  • 5
    NVIDIA Triton Inference Server
    NVIDIA Triton™ inference server delivers fast and scalable AI in production. Open-source inference serving software, Triton inference server streamlines AI inference by enabling teams deploy trained AI models from any framework (TensorFlow, NVIDIA TensorRT®, PyTorch, ONNX, XGBoost, Python, custom and more on any GPU- or CPU-based infrastructure (cloud, data center, or edge). Triton runs models concurrently on GPUs to maximize throughput and utilization, supports x86 and ARM CPU-based inferencing, and offers features like dynamic batching, model analyzer, model ensemble, and audio streaming. Triton helps developers deliver high-performance inference aTriton integrates with Kubernetes for orchestration and scaling, exports Prometheus metrics for monitoring, supports live model updates, and can be used in all major public cloud machine learning (ML) and managed Kubernetes platforms. Triton helps standardize model deployment in production.
    Starting Price: Free
  • 6
    BentoML

    BentoML

    BentoML

    Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.
    Starting Price: Free
  • 7
    Flyte

    Flyte

    Union.ai

    The workflow automation platform for complex, mission-critical data and ML processes at scale. Flyte makes it easy to create concurrent, scalable, and maintainable workflows for machine learning and data processing. Flyte is used in production at Lyft, Spotify, Freenome, and others. At Lyft, Flyte has been serving production model training and data processing for over four years, becoming the de-facto platform for teams like pricing, locations, ETA, mapping, autonomous, and more. In fact, Flyte manages over 10,000 unique workflows at Lyft, totaling over 1,000,000 executions every month, 20 million tasks, and 40 million containers. Flyte has been battle-tested at Lyft, Spotify, Freenome, and others. It is entirely open-source with an Apache 2.0 license under the Linux Foundation with a cross-industry overseeing committee. Configuring machine learning and data workflows can get complex and error-prone with YAML.
    Starting Price: Free
  • 8
    Sedai

    Sedai

    Sedai

    Sedai is an autonomous cloud management platform powered by AI/ML delivering continuous optimization for cloud operations teams to maximize cloud cost savings, performance and availability at scale. Sedai enables teams to shift from static rules and threshold-based automation to modern ML-based autonomous operations. Using Sedai, organizations can reduce cloud cost by up to 50%, improve performance by up to 75%, reduce failed customer interactions (FCIs) by 75% and multiply SRE productivity by up to 6X for their modern applications. Sedai can perform work equivalent to a team of cloud engineers working behind the scenes to optimize resources and remediate issues, so organizations can focus on innovation.
    Starting Price: $10 per month
  • 9
    Giskard

    Giskard

    Giskard

    Giskard provides interfaces for AI & Business teams to evaluate and test ML models through automated tests and collaborative feedback from all stakeholders. Giskard speeds up teamwork to validate ML models and gives you peace of mind to eliminate risks of regression, drift, and bias before deploying ML models to production.
    Starting Price: $0
  • 10
    InsightFinder

    InsightFinder

    InsightFinder

    InsightFinder Unified Intelligence Engine (UIE) platform provides human-centered AI solutions for identifying incident root causes, and predicting and preventing production incidents. Powered by patented self-tuning unsupervised machine learning, InsightFinder continuously learns from metric time series, logs, traces, and triage threads from SREs and DevOps Engineers to bubble up root causes and predict incidents from the source. Companies of all sizes have embraced the platform and seen that business-impacting incidents can be predicted hours ahead with clearly pinpointed root causes. Survey a comprehensive overview of your IT Ops ecosystem, including patterns, trends, and team activities. Also view calculations that demonstrate overall downtime savings, cost of labor savings, and number of incidents resolved.
    Starting Price: $2.5 per core per month
  • 11
    TrueFoundry

    TrueFoundry

    TrueFoundry

    TrueFoundry is a Cloud-native Machine Learning Training and Deployment PaaS on top of Kubernetes that enables Machine learning teams to train and Deploy models at the speed of Big Tech with 100% reliability and scalability - allowing them to save cost and release Models to production faster. We abstract out the Kubernetes for Data Scientists and enable them to operate in a way they are comfortable. It also allows teams to deploy and fine-tune large language models seamlessly with full security and cost optimization. TrueFoundry is open-ended, API Driven and integrates with the internal systems, deploys on a company's internal infrastructure and ensures complete Data Privacy and DevSecOps practices.
    Starting Price: $5 per month
  • 12
    Milvus

    Milvus

    Zilliz

    Vector database built for scalable similarity search. Open-source, highly scalable, and blazing fast. Store, index, and manage massive embedding vectors generated by deep neural networks and other machine learning (ML) models. With Milvus vector database, you can create a large-scale similarity search service in less than a minute. Simple and intuitive SDKs are also available for a variety of different languages. Milvus is hardware efficient and provides advanced indexing algorithms, achieving a 10x performance boost in retrieval speed. Milvus vector database has been battle-tested by over a thousand enterprise users in a variety of use cases. With extensive isolation of individual system components, Milvus is highly resilient and reliable. The distributed and high-throughput nature of Milvus makes it a natural fit for serving large-scale vector data. Milvus vector database adopts a systemic approach to cloud-nativity, separating compute from storage.
    Starting Price: Free
  • 13
    Vald

    Vald

    Vald

    Vald is a highly scalable distributed fast approximate nearest neighbor dense vector search engine. Vald is designed and implemented based on the Cloud-Native architecture. It uses the fastest ANN Algorithm NGT to search neighbors. Vald has automatic vector indexing and index backup, and horizontal scaling which made for searching from billions of feature vector data. Vald is easy to use, feature-rich and highly customizable as you needed. Usually the graph requires locking during indexing, which cause stop-the-world. But Vald uses distributed index graph so it continues to work during indexing. Vald implements its own highly customizable Ingress/Egress filter. Which can be configured to fit the gRPC interface. Horizontal scalable on memory and cpu for your demand. Vald supports to auto backup feature using Object Storage or Persistent Volume which enables disaster recovery.
    Starting Price: Free
  • 14
    ZenML

    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
  • 15
    Azure AI Document Intelligence
    AI Document Intelligence is an AI service that applies advanced machine learning to extract text, key-value pairs, tables, and structures from documents automatically and accurately. Turn documents into usable data and shift your focus to acting on information rather than compiling it. Start with prebuilt models or create custom models tailored to your documents both on-premises and in the cloud with the AI Document Intelligence studio or SDK. Learn how to accelerate your business processes by automating text extraction with AI Document Intelligence. This webinar features hands-on demos for key use cases such as document processing, knowledge mining, and industry-specific AI model customization. Accurately extract text, key-value pairs, and tables from documents, forms, receipts, invoices, and cards of various types without manual labeling by document type, intensive coding, or maintenance. Use AI Document Intelligence custom forms, prebuilt, and layout APIs to extract information.
    Starting Price: $1.50 per 1,000 pages
  • 16
    BudgetML
    BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end. We built BudgetML because it's hard to find a simple way to get a model in production quickly and cheaply. Cloud functions are limited in memory and cost a lot at scale. Kubernetes clusters are overkill for one single model. Deploying from scratch involves learning too many different concepts like SSL certificate generation, Docker, REST, Uvicorn/Gunicorn, backend servers, etc., that are simply not within the scope of a typical data scientist. BudgetML is our answer to this challenge. It is supposed to be fast, easy, and developer-friendly. It is by no means meant to be used in a full-fledged production-ready setup. It is simply a means to get a server up and running as fast as possible with the lowest costs possible.
    Starting Price: Free
  • 17
    Tembo

    Tembo

    Tembo

    Tembo is an AI-powered engineering assistant designed to automate routine coding tasks, helping developers focus on innovation. It monitors systems 24/7 to identify and fix production errors automatically, transforming error logs into pull requests while you sleep. Tembo optimizes database performance by diagnosing slow queries and missing indexes, improving efficiency. It integrates seamlessly with tools like GitHub, Jira, Linear, and Datadog to convert tickets and error reports into actionable code changes. The platform also explores codebases to uncover technical debt and security issues for refactoring opportunities. Trusted by teams worldwide, Tembo accelerates development velocity by automating tedious engineering work.
    Starting Price: $50
  • 18
    VESSL AI

    VESSL AI

    VESSL AI

    Build, train, and deploy models faster at scale with fully managed infrastructure, tools, and workflows. Deploy custom AI & LLMs on any infrastructure in seconds and scale inference with ease. Handle your most demanding tasks with batch job scheduling, only paying with per-second billing. Optimize costs with GPU usage, spot instances, and built-in automatic failover. Train with a single command with YAML, simplifying complex infrastructure setups. Automatically scale up workers during high traffic and scale down to zero during inactivity. Deploy cutting-edge models with persistent endpoints in a serverless environment, optimizing resource usage. Monitor system and inference metrics in real-time, including worker count, GPU utilization, latency, and throughput. Efficiently conduct A/B testing by splitting traffic among multiple models for evaluation.
    Starting Price: $100 + compute/month
  • 19
    Lunary

    Lunary

    Lunary

    Lunary is an AI developer platform designed to help AI teams manage, improve, and protect Large Language Model (LLM) chatbots. It offers features such as conversation and feedback tracking, analytics on costs and performance, debugging tools, and a prompt directory for versioning and team collaboration. Lunary supports integration with various LLMs and frameworks, including OpenAI and LangChain, and provides SDKs for Python and JavaScript. Guardrails to deflect malicious prompts and sensitive data leaks. Deploy in your VPC with Kubernetes or Docker. Allow your team to judge responses from your LLMs. Understand what languages your users are speaking. Experiment with prompts and LLM models. Search and filter anything in milliseconds. Receive notifications when agents are not performing as expected. Lunary's core platform is 100% open-source. Self-host or in the cloud, get started in minutes.
    Starting Price: $20 per month
  • 20
    txtai

    txtai

    NeuML

    txtai is an all-in-one open source embeddings database designed for semantic search, large language model orchestration, and language model workflows. It unifies vector indexes (both sparse and dense), graph networks, and relational databases, providing a robust foundation for vector search and serving as a powerful knowledge source for LLM applications. With txtai, users can build autonomous agents, implement retrieval augmented generation processes, and develop multi-modal workflows. Key features include vector search with SQL support, object storage integration, topic modeling, graph analysis, and multimodal indexing capabilities. It supports the creation of embeddings for various data types, including text, documents, audio, images, and video. Additionally, txtai offers pipelines powered by language models that handle tasks such as LLM prompting, question-answering, labeling, transcription, translation, and summarization.
    Starting Price: Free
  • 21
    Windmill

    Windmill

    Windmill

    ​Windmill is an open source developer platform and workflow engine that transforms scripts into auto-generated UIs, APIs, and cron jobs, enabling the composition of workflows or data pipelines for building complex, data-intensive applications with ease. Supporting various languages, Windmill allows users to write and deploy software up to ten times faster, operating with high reliability and observability on a self-hostable job orchestrator. It features auto-generated user interfaces based on script parameters, a low-code app editor for creating custom UIs, and a flow editor for constructing workflows using a drag-and-drop interface. Windmill manages dependencies automatically, offers robust permissioning and monitoring, and provides various triggers including webhooks, schedules, CLI, Slack, and emails. Users can develop scripts locally with their preferred code editors, preview them, and deploy using the CLI.
    Starting Price: $120 per month
  • 22
    FriendliAI

    FriendliAI

    FriendliAI

    FriendliAI is a generative AI infrastructure platform that offers fast, efficient, and reliable inference solutions for production environments. It provides a suite of tools and services designed to optimize the deployment and serving of large language models (LLMs) and other generative AI workloads at scale. Key offerings include Friendli Endpoints, which allow users to build and serve custom generative AI models, saving GPU costs and accelerating AI inference. It supports seamless integration with popular open source models from the Hugging Face Hub, enabling lightning-fast, high-performance inference. FriendliAI's cutting-edge technologies, such as Iteration Batching, Friendli DNN Library, Friendli TCache, and Native Quantization, contribute to significant cost savings (50–90%), reduced GPU requirements (6× fewer GPUs), higher throughput (10.7×), and lower latency (6.2×).
    Starting Price: $5.9 per hour
  • 23
    Kodosumi

    Kodosumi

    Masumi

    Kodosumi is an open source, framework-agnostic runtime environment built on Ray for deploying, managing, and scaling agentic services at the enterprise level. It enables effortless deployment of AI agents with a single YAML config, offering minimal setup overhead and no vendor lock-in. Designed for handling bursty traffic and long-running workflows, it dynamically scales across Ray clusters to ensure consistent performance. Kodosumi integrates real-time logging and monitoring through the Ray dashboard, providing instant observability and streamlined debugging of complex flows. Core building blocks include autonomous agents (task performers), orchestrated flows, and deployable agentic services, all managed via a pragmatic web admin panel.
    Starting Price: Free
  • 24
    Dash0

    Dash0

    Dash0

    Dash0 is an OpenTelemetry-native observability platform that unifies metrics, logs, traces, and resources into one intuitive interface, enabling fast and context-rich monitoring without vendor lock-in. It centralizes Prometheus and OpenTelemetry metrics, supports powerful filtering of high-cardinality attributes, and provides heatmap drilldowns and detailed trace views to pinpoint errors and bottlenecks in real time. Users benefit from fully customizable dashboards built on Perses, with support for code-based configuration and Grafana import, plus seamless integration with predefined alerts, checks, and PromQL queries. Dash0's AI-enhanced tools, such as Log AI for automated severity inference and pattern extraction, enrich telemetry data without requiring users to even notice that AI is working behind the scenes. These AI capabilities power features like log classification, grouping, inferred severity tagging, and streamlined triage workflows through the SIFT framework.
    Starting Price: $0.20 per month
  • 25
    Codacy

    Codacy

    Codacy

    Codacy is an automated code review tool that helps identify issues through static code analysis, allowing engineering teams to save time in code reviews and tackle technical debt. Codacy integrates seamlessly into existing workflows on your Git provider, and also with Slack, JIRA, or using Webhooks. Users receive notifications on security issues, code coverage, code duplication, and code complexity in every commit and pull request along with advanced code metrics on the health of a project and team performance. The Codacy CLI enables running Codacy code analysis locally, so teams can see Codacy results without having to check their Git provider or the Codacy app. Codacy supports more than 30 coding languages and is available in free open-source, and enterprise versions (cloud and self-hosted). For more see https://www.codacy.com/
    Starting Price: $15.00/month/user
  • 26
    Mendix

    Mendix

    Mendix

    Mendix, a Siemens business and the global leader in enterprise low-code, is fundamentally reinventing the way applications are delivered in the digital enterprise. With the Mendix platform, enterprises can ‘Make with More,’ by broadening their development capability to conquer the software development bottleneck; ‘Make it Smart,’ by making apps with rich native experiences that are intelligent, proactive, and contextual; and ‘Make at Scale,’ to modernize core systems and build large app portfolios. The Mendix platform is built to promote intense collaboration between business and IT teams and dramatically accelerate application development cycles while maintaining the highest security, quality, and governance, in short, to help enterprises leap into their digital futures. The Mendix platform has been adopted by more than 4,000 leading companies around the world including Conoco Phillips, Business Development Bank of Canada, Post NL, Continental, Zurich Insurance, and
  • 27
    AllegroGraph

    AllegroGraph

    Franz Inc.

    AllegroGraph is a breakthrough solution that allows infinite data integration through a patented approach unifying all data and siloed knowledge into an Entity-Event Knowledge Graph solution that can support massive big data analytics. AllegroGraph utilizes unique federated sharding capabilities that drive 360-degree insights and enable complex reasoning across a distributed Knowledge Graph. AllegroGraph provides users with an integrated version of Gruff, a unique browser-based graph visualization software tool for exploring and discovering connections within enterprise Knowledge Graphs. Franz’s Knowledge Graph Solution includes both technology and services for building industrial strength Entity-Event Knowledge Graphs based on best-of-class tools, products, knowledge, skills and experience.
  • 28
    RazorThink

    RazorThink

    RazorThink

    RZT aiOS offers all of the benefits of a unified artificial intelligence platform and more, because it's not just a platform — it's a comprehensive Operating System that fully connects, manages and unifies all of your AI initiatives. And, AI developers now can do in days what used to take them months, because aiOS process management dramatically increases the productivity of AI teams. This Operating System offers an intuitive environment for AI development, letting you visually build models, explore data, create processing pipelines, run experiments, and view analytics. What's more is that you can do it all even without advanced software engineering skills.
  • 29
    Google Deep Learning Containers
    Build your deep learning project quickly on Google Cloud: Quickly prototype with a portable and consistent environment for developing, testing, and deploying your AI applications with Deep Learning Containers. These Docker images use popular frameworks and are performance optimized, compatibility tested, and ready to deploy. Deep Learning Containers provide a consistent environment across Google Cloud services, making it easy to scale in the cloud or shift from on-premises. You have the flexibility to deploy on Google Kubernetes Engine (GKE), AI Platform, Cloud Run, Compute Engine, Kubernetes, and Docker Swarm.
  • 30
    Deepgram

    Deepgram

    Deepgram

    Deploy accurate speech recognition at scale while continuously improving model performance by labeling data and training from a single console. We deliver state-of-the-art speech recognition and understanding at scale. We do it by providing cutting-edge model training and data-labeling alongside flexible deployment options. Our platform recognizes multiple languages, accents, and words, dynamically tuning to the needs of your business with every training session. The fastest, most accurate, most reliable, most scalable speech transcription, with understanding — rebuilt just for enterprise. We’ve reinvented ASR with 100% deep learning that allows companies to continuously improve accuracy. Stop waiting for the big tech players to improve their software and forcing your developers to manually boost accuracy with keywords in every API call. Start training your speech model and reaping the benefits in weeks, not months or years.
    Starting Price: $0