Find and compare the best Artificial Intelligence software for Kubernetes in 2025
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Use the comparison tool below to compare the top Artificial Intelligence software for Kubernetes on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Darktrace
Darktrace
Darktrace offers a cutting-edge cybersecurity solution with its ActiveAI Security Platform, which utilizes AI to ensure proactive and real-time defense against cyber threats. The platform continually monitors enterprise data, from emails and cloud infrastructure to endpoints and applications, providing a detailed, contextual understanding of the security landscape. Darktrace’s AI-driven system autonomously investigates alerts, correlates incidents, and responds to both known and unknown threats, ensuring that businesses stay one step ahead of adversaries. By automating investigations and recovery actions, Darktrace reduces the burden on security teams and speeds up incident response, driving efficiency and improving cyber resilience. With a significant reduction in containment time and faster SOC triage, Darktrace ensures businesses are better protected from ever-evolving threats. -
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SOAtest
Parasoft
PARASOFT SOATEST Artificial Intelligence and Machine Learning Power APIs and Web Service Testing Tools Parasoft SOAtest is based on artificial intelligence (AI), machine learning (ML), and simplifies functional testing across APIs and UIs. The API and web service testing tool is perfect for Agile DevOps environments because it uses continuous quality monitoring systems to monitor the quality of change management systems. Parasoft SOAtest is a fully integrated API and web-service testing tool that automates end-to-end functional API test automation. Automated testing is simplified with advanced functional test-creation capabilities. This applies to applications with multiple interfaces (REST and SOAP APIs as well as microservices, databases, etc.). These tools reduce security breaches and performance issues by turning functional testing artifacts in security and load equivalents. This allows for faster and more efficient testing, while also allowing continuous monitoring of API changes. -
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MLflow
MLflow
MLflow is an open-source suite designed to oversee the machine learning lifecycle, encompassing aspects such as experimentation, reproducibility, deployment, and a centralized model registry. The platform features four main components that facilitate various tasks: tracking and querying experiments encompassing code, data, configurations, and outcomes; packaging data science code to ensure reproducibility across multiple platforms; deploying machine learning models across various serving environments; and storing, annotating, discovering, and managing models in a unified repository. Among these, the MLflow Tracking component provides both an API and a user interface for logging essential aspects like parameters, code versions, metrics, and output files generated during the execution of machine learning tasks, enabling later visualization of results. It allows for logging and querying experiments through several interfaces, including Python, REST, R API, and Java API. Furthermore, an MLflow Project is a structured format for organizing data science code, ensuring it can be reused and reproduced easily, with a focus on established conventions. Additionally, the Projects component comes equipped with an API and command-line tools specifically designed for executing these projects effectively. Overall, MLflow streamlines the management of machine learning workflows, making it easier for teams to collaborate and iterate on their models. -
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EVA.ai
EVA.ai
EVA.ai's HR Tech Automation Platform effectively enhances enterprise operations by tailoring the experiences of Talent, Recruiters, and Leaders on a large scale. This innovation represents the fourth industrial revolution within the realms of talent acquisition, management, and engagement. By adhering to an automation-first philosophy, EVA empowers organizations to grow by integrating advanced technologies with user-centric solutions that minimize inefficiencies and dissatisfaction throughout the human capital management lifecycle. With EVABot, your digital conversational assistant, you can elevate the candidate experience while boosting the productivity of hiring teams through 'outcome-based' automation and machine learning. Additionally, this platform equips hiring managers with real-time process visibility, enabling them to make informed decisions. By providing the necessary tools for effectiveness, EVA ensures that the talent acquisition process delivers meaningful experiences for candidates, HR executives, and hiring managers at every interaction point along the hiring journey. Ultimately, this comprehensive approach fosters a more efficient and engaging recruitment experience for all stakeholders involved. -
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Deep learning frameworks like TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have significantly enhanced the accessibility of deep learning by simplifying the design, training, and application of deep learning models. Fabric for Deep Learning (FfDL, pronounced “fiddle”) offers a standardized method for deploying these deep-learning frameworks as a service on Kubernetes, ensuring smooth operation. The architecture of FfDL is built on microservices, which minimizes the interdependence between components, promotes simplicity, and maintains a stateless nature for each component. This design choice also helps to isolate failures, allowing for independent development, testing, deployment, scaling, and upgrading of each element. By harnessing the capabilities of Kubernetes, FfDL delivers a highly scalable, resilient, and fault-tolerant environment for deep learning tasks. Additionally, the platform incorporates a distribution and orchestration layer that enables efficient learning from large datasets across multiple compute nodes within a manageable timeframe. This comprehensive approach ensures that deep learning projects can be executed with both efficiency and reliability.
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Disruptica
Disruptica
Delivering cutting-edge solutions that merge artificial intelligence with software engineering is our goal. We believe that AI and automation should be seamlessly integrated into everyday use, which is why we create specialized micro apps tailored for specific industry needs, such as applications for fraud detection, risk assessment, and sales predictions. Utilize our application estimator tool to gain insights into potential project expenses. We understand the complications of monolithic architecture, so we focus on developing both front and back-end microservice applications that offer a more adaptable, scalable, and contemporary solution. Additionally, we have our own open-source platform that enables us to modify, enhance, or completely overhaul sections of an application with ease, ensuring that our software remains secure and dependable. Begin your journey in application development while incorporating AI and automation through our robust architectural framework today! Furthermore, we not only create innovative solutions but also offer comprehensive technical strategic plans that empower businesses to effectively implement, assess, or expand their AI initiatives. This holistic approach ensures clients are well-equipped to navigate the complexities of modern technology. -
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Kubeflow
Kubeflow
The Kubeflow initiative aims to simplify the process of deploying machine learning workflows on Kubernetes, ensuring they are both portable and scalable. Rather than duplicating existing services, our focus is on offering an easy-to-use platform for implementing top-tier open-source ML systems across various infrastructures. Kubeflow is designed to operate seamlessly wherever Kubernetes is running. It features a specialized TensorFlow training job operator that facilitates the training of machine learning models, particularly excelling in managing distributed TensorFlow training tasks. Users can fine-tune the training controller to utilize either CPUs or GPUs, adapting it to different cluster configurations. In addition, Kubeflow provides functionalities to create and oversee interactive Jupyter notebooks, allowing for tailored deployments and resource allocation specific to data science tasks. You can test and refine your workflows locally before transitioning them to a cloud environment whenever you are prepared. This flexibility empowers data scientists to iterate efficiently, ensuring that their models are robust and ready for production. -
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Polyaxon
Polyaxon
A comprehensive platform designed for reproducible and scalable applications in Machine Learning and Deep Learning. Explore the array of features and products that support the leading platform for managing data science workflows today. Polyaxon offers an engaging workspace equipped with notebooks, tensorboards, visualizations, and dashboards. It facilitates team collaboration, allowing members to share, compare, and analyze experiments and their outcomes effortlessly. With built-in version control, you can achieve reproducible results for both code and experiments. Polyaxon can be deployed in various environments, whether in the cloud, on-premises, or in hybrid setups, ranging from a single laptop to container management systems or Kubernetes. Additionally, you can easily adjust resources by spinning up or down, increasing the number of nodes, adding GPUs, and expanding storage capabilities as needed. This flexibility ensures that your data science projects can scale effectively to meet growing demands. -
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CoreWeave
CoreWeave
CoreWeave stands out as a cloud infrastructure service that focuses on GPU-centric computing solutions specifically designed for artificial intelligence applications. Their platform delivers scalable, high-performance GPU clusters that enhance both training and inference processes for AI models, catering to sectors such as machine learning, visual effects, and high-performance computing. In addition to robust GPU capabilities, CoreWeave offers adaptable storage, networking, and managed services that empower AI-focused enterprises, emphasizing reliability, cost-effectiveness, and top-tier security measures. This versatile platform is widely adopted by AI research facilities, labs, and commercial entities aiming to expedite their advancements in artificial intelligence technology. By providing an infrastructure that meets the specific demands of AI workloads, CoreWeave plays a crucial role in driving innovation across various industries. -
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NVIDIA Riva Studio
NVIDIA
Utilize a browser equipped with in-app prompts alongside a recording tool to gather audio samples. You can access a curated collection of phonetically balanced sentences designed to help build a 30-minute dataset aimed at training a TTS model that captures the nuances of your distinct voice. Tailor the model's sound by selecting the pitch range that aligns best with your vocal characteristics, as a suggested typical voice pitch range setting is already included, along with a preconfigured optimal recipe for personalizing the TTS model to reflect your voice. To further enhance functionality, create an API that allows seamless integration of your customized TTS model into various applications. You’ll also have the option to download a deployable package that includes a helm chart, facilitating deployment on any cloud platform or an on-premises Kubernetes cluster. Following that, you can effortlessly host your voice microservice using NVIDIA or implement it with a simple line of code, ensuring smooth operation. Additionally, the Riva TTS model can be set up, customized, and deployed through user-friendly no-code, end-to-end graphical workflows, eliminating the need for intricate infrastructure configuration, and making the process accessible for everyone. This approach not only streamlines the deployment process but also empowers users to create high-quality TTS solutions with minimal technical barriers. -
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Outerbounds
Outerbounds
Create and execute data-heavy projects using the user-friendly, open-source Metaflow framework. The Outerbounds platform offers a completely managed environment to run, scale, and deploy these projects with reliability. It serves as a comprehensive solution for all your machine learning and data science endeavors. You can securely access data from your current data warehouses and utilize a computing cluster that is tailored for both scalability and cost-effectiveness. With 24/7 managed orchestration, production workflows are streamlined and efficient. Results can be leveraged to enhance any application, empowering your data scientists while receiving approval from engineers. The Outerbounds Platform enables rapid development, large-scale experimentation, and confident production deployment, all while adhering to the policies set by your engineers and operating securely within your cloud account. Security is fundamentally integrated into our platform rather than being an afterthought. It meets your compliance needs through various layers of security measures, including centralized authentication, a strict permission framework, and clearly defined roles for task execution, ensuring that your data and processes remain safe. This cohesive structure allows teams to collaborate effectively while maintaining control over their data environment. -
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UBOS
UBOS
Unlock the potential to turn your innovative concepts into AI applications within moments. Our no-code/low-code platform empowers everyone, from seasoned developers to everyday business users, to craft cutting-edge AI-based applications in just 10 minutes. Effortlessly connect with APIs such as ChatGPT, Dall-E 2, and Codex from OpenAI, along with the ability to implement custom machine learning models. You can create tailored admin clients and CRUD functionalities, enabling efficient management of sales, inventory, contracts, and beyond. Develop interactive dashboards that convert data into insightful actions, driving innovation within your organization. Additionally, easily set up a chatbot to enhance customer support and create a truly omnichannel experience through various integrations. This comprehensive cloud platform harmonizes low-code/no-code tools with advanced technologies, ensuring your web applications are scalable, secure, and straightforward to oversee. Revolutionize your software development journey with our versatile no-code/low-code platform, which is ideal for both business users and skilled developers, paving the way for limitless possibilities. Moreover, the user-friendly interface ensures that anyone can get started quickly, making technology accessible to all. -
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Selenic
Parasoft
Selenium tests often suffer from instability and maintenance challenges. Parasoft Selenic addresses prevalent issues in your existing Selenium projects without imposing vendor restrictions. When your team relies on Selenium for developing and testing the user interface of software applications, it's crucial to ensure that the testing process effectively uncovers genuine problems, formulates relevant and high-quality tests, and minimizes maintenance efforts. Although Selenium provides numerous advantages, maximizing the efficiency of your UI testing while utilizing your current processes is essential. With Parasoft Selenic, you can pinpoint actual UI problems and receive prompt feedback on test outcomes, enabling you to deliver superior software more swiftly. You can enhance your existing library of Selenium web UI tests or quickly generate new ones using a versatile companion that integrates effortlessly into your setup. Parasoft Selenic employs AI-driven self-healing to resolve frequent Selenium issues, significantly reduces test execution time through impact analysis, and provides additional features to streamline your testing workflow. Ultimately, this tool empowers your team to achieve more effective and reliable testing results. -
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Second State
Second State
Lightweight, fast, portable, and powered by Rust, our solution is designed to be compatible with OpenAI. We collaborate with cloud providers, particularly those specializing in edge cloud and CDN compute, to facilitate microservices tailored for web applications. Our solutions cater to a wide array of use cases, ranging from AI inference and database interactions to CRM systems, ecommerce, workflow management, and server-side rendering. Additionally, we integrate with streaming frameworks and databases to enable embedded serverless functions aimed at data filtering and analytics. These serverless functions can serve as database user-defined functions (UDFs) or be integrated into data ingestion processes and query result streams. With a focus on maximizing GPU utilization, our platform allows you to write once and deploy anywhere. In just five minutes, you can start utilizing the Llama 2 series of models directly on your device. One of the prominent methodologies for constructing AI agents with access to external knowledge bases is retrieval-augmented generation (RAG). Furthermore, you can easily create an HTTP microservice dedicated to image classification that operates YOLO and Mediapipe models at optimal GPU performance, showcasing our commitment to delivering efficient and powerful computing solutions. This capability opens the door for innovative applications in fields such as security, healthcare, and automatic content moderation. -
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Blink
Blink Ops
Blink serves as a powerful ROI enhancer for security teams and business executives aiming to efficiently secure an extensive range of scenarios. It provides comprehensive visibility and coverage of alerts throughout your organization and security infrastructure. By leveraging automated processes, it minimizes noise and decreases the incidence of false alarms in alerts. Additionally, it scans for attacks while proactively detecting insider threats and vulnerabilities. Users can establish automated workflows that incorporate pertinent context, simplify communication, and shorten mean time to resolution (MTTR). Alerts can be acted upon to bolster your cloud security posture through no-code automation and generative AI. The platform also facilitates shift-left access requests, streamlines approval processes, and allows developers to work without hindrance, all while ensuring application security. Furthermore, it enables ongoing monitoring of applications for compliance with SOC2, ISO, GDPR, and other standards, helping to enforce necessary controls. This comprehensive approach not only improves security but also enhances operational efficiency across the board. -
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Docu Dig
Docu Dig
Docu Dig serves as an innovative solution for businesses seeking effortless and secure methods to search for content and gain insights from their documents. Enhance your organization's ability to extract valuable information with a tailored Docu Dig experience. Harness the power of AI-driven smart search capabilities to unlock the full potential of your documents while ensuring security. Utilizing state-of-the-art AI technology, Docu Dig significantly improves the retrieval of document insights, thereby increasing team efficiency and facilitating easier access to vital information. At the core of Docu Dig's philosophy is a commitment to data security, employing sophisticated encryption techniques to safeguard your documents both when stored and during transmission. For organizations handling highly sensitive information, we offer dedicated, sandboxed AI models either in the cloud or via on-premises physical servers, ensuring your data remains within your control. Unlike conventional methods that rely solely on precise keyword matching, our AI is adept at grasping the context of your inquiries, delivering accurate insights from the documents you select, ultimately revolutionizing the way you interact with your data. Experience a new era of document management that prioritizes security and efficiency with Docu Dig. -
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RTMaps
Intempora
RTMaps is a component-based middleware for development and execution that is highly optimized. RTMaps allows developers to design complex real-time algorithms and systems for their autonomous applications, such as mobile robots and railways. RTMaps offers a variety of benefits to help you develop and execute an application. • Asynchronous data acquisition • Optimised performance • Synchronized recording and playback • Comprehensive component libraries: Over 600 I/O components available • Flexible algorithm development - Share and collaborate Multi-platform processing • Scalable and cross-platform: from PCs, embedded targets, to Cloud. • Rapid prototyping & testing • Integration with dSPACE Tools • Time and Resource Savings • Limiting development risks, errors and effort • Certification ISO26262 ASIL-B: on demand -
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ModelOp
ModelOp
ModelOp stands at the forefront of AI governance solutions, empowering businesses to protect their AI projects, including generative AI and Large Language Models (LLMs), while promoting innovation. As corporate leaders push for swift integration of generative AI, they encounter various challenges such as financial implications, regulatory compliance, security concerns, privacy issues, ethical dilemmas, and potential brand damage. With governments at global, federal, state, and local levels rapidly establishing AI regulations and oversight, organizations must act promptly to align with these emerging guidelines aimed at mitigating AI-related risks. Engaging with AI Governance specialists can keep you updated on market dynamics, regulatory changes, news, research, and valuable perspectives that facilitate a careful navigation of the benefits and hazards of enterprise AI. ModelOp Center not only ensures organizational safety but also instills confidence among all stakeholders involved. By enhancing the processes of reporting, monitoring, and compliance across the enterprise, businesses can foster a culture of responsible AI usage. In a landscape that evolves quickly, staying informed and compliant is essential for sustainable success. -
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StackGen
StackGen
Generate secure, context-aware infrastructure as code (IaC) directly from application code without needing to modify that code. While we appreciate the benefits of infrastructure as code, there is certainly potential for enhancements. StackGen leverages the application’s existing code to produce IaC that is not only consistent and secure but also compliant with industry standards. This approach eliminates bottlenecks, reduces potential liabilities, and minimizes the risk of errors that often come from manual processes, allowing for a quicker time-to-market for your applications. By providing developers with a streamlined experience, they can focus on coding rather than having to become infrastructure specialists. Consistency, security, and policy compliance are integrated by default into the auto-generated IaC. The system generates context-aware IaC without requiring any changes to the original code, ensuring that it is properly supported and aligned with the principle of least-privileged access. There's no necessity to reconstruct your existing pipelines, as StackGen seamlessly integrates into your current workflows, bridging the gaps between teams. This empowers developers to automatically create IaC that adheres to your established provisioning checklist, enhancing overall efficiency and collaboration. Ultimately, this innovative approach not only accelerates development but also strengthens security protocols across the board. -
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Operant
Operant AI
Operant AI offers comprehensive protection for all layers of contemporary applications, spanning from infrastructure to APIs. With a straightforward deployment that takes only minutes, Operant ensures complete security visibility and runtime controls, effectively thwarting a variety of both common and critical cyber threats such as data exfiltration, data poisoning, zero-day vulnerabilities, lateral movement, cryptomining, prompt injection, and beyond. This is achieved with no need for instrumentation, no drift, and minimal disruption for Development, Security, and Operations teams. Furthermore, Operant's in-line runtime safeguarding of all data in use during every interaction, from infrastructure to APIs, elevates the defense mechanisms for your cloud-native applications while requiring zero instrumentation, no alterations to application code, and no additional integrations, thus streamlining the security process significantly. -
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Edera
Edera
Introducing AI and Kubernetes that prioritize security from the ground up, regardless of your infrastructure's location. By establishing a robust security boundary around Kubernetes workloads, we eliminate the risks associated with container escapes. Our approach simplifies the execution of AI and machine learning tasks through advanced GPU device virtualization, driver isolation, and virtual GPUs (vGPUs). Edera Krata heralds a transformative shift in isolation technology, paving the way for a new era focused on security. Edera redefines both security and performance for AI and GPU applications, while ensuring seamless integration with Kubernetes environments. Each container operates with its own dedicated Linux kernel, thereby removing the vulnerabilities linked to shared kernel states among containers. This advancement effectively ends the prevalence of container escapes, reduces the need for costly security tools, and alleviates the burden of endlessly sifting through logs. With just a few lines of YAML, you can launch Edera Protect and get started effortlessly. Designed in Rust to enhance memory safety, this solution has no negative impact on performance. It represents a secure-by-design Kubernetes framework that effectively neutralizes threats before they can take action, transforming the landscape of cloud-native security. -
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Stratio
Stratio
A comprehensive and secure business data layer that delivers immediate insights for both business and data teams is essential. Stratio's generative AI data fabric encompasses the entire data management lifecycle, including data discovery, governance, utilization, and eventual disposal. In many organizations, data is scattered across various divisions, with different applications employed for distinct tasks. Stratio harnesses the power of AI to locate and access all your data, regardless of whether it resides on-premises or in the cloud. This ensures that your organization handles data in an appropriate manner. If you cannot visualize your data as soon as it is generated, you risk falling behind your customers' needs. Conventional data infrastructures often require hours to process customer data, hindering responsiveness. Stratio, however, enables real-time access to 100% of your data without necessitating its relocation, allowing you to respond swiftly while maintaining crucial context. Ultimately, by integrating operational and informational aspects within a collaborative platform, organizations can transition to leveraging instant extended AI capabilities for enhanced decision-making and agility. Embracing such a unified approach will empower businesses to thrive in a data-driven landscape. -
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Simplismart
Simplismart
Enhance and launch AI models using Simplismart's ultra-fast inference engine. Seamlessly connect with major cloud platforms like AWS, Azure, GCP, and others for straightforward, scalable, and budget-friendly deployment options. Easily import open-source models from widely-used online repositories or utilize your personalized custom model. You can opt to utilize your own cloud resources or allow Simplismart to manage your model hosting. With Simplismart, you can go beyond just deploying AI models; you have the capability to train, deploy, and monitor any machine learning model, achieving improved inference speeds while minimizing costs. Import any dataset for quick fine-tuning of both open-source and custom models. Efficiently conduct multiple training experiments in parallel to enhance your workflow, and deploy any model on our endpoints or within your own VPC or on-premises to experience superior performance at reduced costs. The process of streamlined and user-friendly deployment is now achievable. You can also track GPU usage and monitor all your node clusters from a single dashboard, enabling you to identify any resource limitations or model inefficiencies promptly. This comprehensive approach to AI model management ensures that you can maximize your operational efficiency and effectiveness. -
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Ludwig
Uber AI
Ludwig serves as a low-code platform specifically designed for the development of tailored AI models, including large language models (LLMs) and various deep neural networks. With Ludwig, creating custom models becomes a straightforward task; you only need a simple declarative YAML configuration file to train an advanced LLM using your own data. It offers comprehensive support for learning across multiple tasks and modalities. The framework includes thorough configuration validation to identify invalid parameter combinations and avert potential runtime errors. Engineered for scalability and performance, it features automatic batch size determination, distributed training capabilities (including DDP and DeepSpeed), parameter-efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and the ability to handle larger-than-memory datasets. Users enjoy expert-level control, allowing them to manage every aspect of their models, including activation functions. Additionally, Ludwig facilitates hyperparameter optimization, offers insights into explainability, and provides detailed metric visualizations. Its modular and extensible architecture enables users to experiment with various model designs, tasks, features, and modalities with minimal adjustments in the configuration, making it feel like a set of building blocks for deep learning innovations. Ultimately, Ludwig empowers developers to push the boundaries of AI model creation while maintaining ease of use. -
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Nutanix Enterprise AI
Nutanix
Nutanix Enterprise AI makes it simple to deploy, operate, and develop enterprise AI applications through secure AI endpoints that utilize large language models and generative AI APIs. By streamlining the process of integrating GenAI, Nutanix enables organizations to unlock extraordinary productivity boosts, enhance revenue streams, and realize the full potential of generative AI. With user-friendly workflows, you can effectively monitor and manage AI endpoints, allowing you to tap into your organization's AI capabilities. The platform's point-and-click interface facilitates the effortless deployment of AI models and secure APIs, giving you the flexibility to select from Hugging Face, NVIDIA NIM, or your customized private models. You have the option to run enterprise AI securely, whether on-premises or in public cloud environments, all while utilizing your existing AI tools. The system also allows for straightforward management of access to your language models through role-based access controls and secure API tokens designed for developers and GenAI application owners. Additionally, with just a single click, you can generate URL-ready JSON code, making API testing quick and efficient. This comprehensive approach ensures that enterprises can fully leverage their AI investments and adapt to evolving technological landscapes seamlessly.