KServe Alternatives

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.

Amazon SageMaker makes it easy to deploy ML models to make predictions (also known as inference) at the best price-performance for any use case. It provides a broad selection of ML infrastructure and model deployment options to help meet all your ML inference needs. It is a fully managed service and integrates with MLOps tools, so you can scale your model deployment, reduce inference costs, manage models more effectively in production, and reduce operational burden. From low latency (a few milliseconds) and high throughput (hundreds of thousands of requests per second) to long-running inference for use cases such as natural language processing and computer vision, you can use Amazon SageMaker for all your inference needs.

Powerful, self-serve machine learning platform where you can turn models into scalable APIs in just a few clicks. Sign up for Deep Infra account using GitHub or log in using GitHub. Choose among hundreds of the most popular ML models. Use a simple rest API to call your model. Deploy models to production faster and cheaper with our serverless GPUs than developing the infrastructure yourself. We have different pricing models depending on the model used. Some of our language models offer per-token pricing. Most other models are billed for inference execution time. With this pricing model, you only pay for what you use. There are no long-term contracts or upfront costs, and you can easily scale up and down as your business needs change. All models run on A100 GPUs, optimized for inference performance and low latency. Our system will automatically scale the model based on your needs.

The always-free NGINX Service Mesh scales from open source projects to a fully supported, secure, and scalable enterprise‑grade solution. Take control of Kubernetes with NGINX Service Mesh, featuring a unified data plane for ingress and egress management in a single configuration. The real star of NGINX Service Mesh is the fully integrated, high-performance data plane. Leveraging the power of NGINX Plus to operate highly available and scalable containerized environments, our data plane brings a level of enterprise traffic management, performance, and scalability to the market that no other sidecars can offer. It provides the seamless and transparent load balancing, reverse proxy, traffic routing, identity, and encryption features needed for production-grade service mesh deployments. When paired with the NGINX Plus-based version of NGINX Ingress Controller, it provides a unified data plane that can be managed with a single configuration.

Mixtral 8x7B is a high-quality sparse mixture of experts model (SMoE) with open weights. Licensed under Apache 2.0. Mixtral outperforms Llama 2 70B on most benchmarks with 6x faster inference. It is the strongest open-weight model with a permissive license and the best model overall regarding cost/performance trade-offs. In particular, it matches or outperforms GPT-3.5 on most standard benchmarks.

Our industry-leading single socket or dual socket high-performance CIARA ORION High Density (HD) servers offer unmatched flexibility, scalability, and efficiency to handle all your critical workloads. The ORION HD products offer the industry’s best density of cores per rackmount unit in order to guarantee optimal rackmount utilization in any data center. Compatible with both Intel® Xeon® Processor Scalable Family and AMD EPYC® processors, ORION High-Density servers provide incredible design options for large-scale deployment of high-density IT and HPC workloads. The ORION high-density server product line is built with the latest silicon technology to provide the best performance, and support of the highest TDP of the industry alongside a vast array of storage options and extensive add-on card support. It is ideal for infrastructure consolidation, academic research, cloud & hosting providers as well as high-performance computing applications.

Flexential's consultative approach to data center solutions and solving the toughest IT challenges goes beyond the four walls of our highly connected, national data center platform. The highly connected FlexAnywhere® platform delivers tailored infrastructure capabilities with automation, a pay-as-you-go model, and high-density scalability for your business needs. The FlexAnywhere platform offers colocation, cloud services, interconnection, data protection, and professional services to support your hybrid IT journey.

With Mystic you can deploy ML in your own Azure/AWS/GCP account or deploy in our shared GPU cluster. All Mystic features are directly in your own cloud. In a few simple steps, you get the most cost-effective and scalable way of running ML inference. Our shared cluster of GPUs is used by 100s of users simultaneously. Low cost but performance will vary depending on real-time GPU availability. Good AI products need good models and infrastructure; we solve the infrastructure part. A fully managed Kubernetes platform that runs in your own cloud. Open-source Python library and API to simplify your entire AI workflow. You get a high-performance platform to serve your AI models. Mystic will automatically scale up and down GPUs depending on the number of API calls your models receive. You can easily view, edit, and monitor your infrastructure from your Mystic dashboard, CLI, and APIs.

Alegion is the data labeling solution for enterprise-grade Machine Learning. We lead the industry in streaming, high-resolution, high-density video annotation, delivering accurately-annotated, model-ready data to train and validate ML models. Alegion provides both the platform and workforce to operate with quality at scale, processing structured and unstructured data including video, image, audio, and text. Our ML powered platform speeds up task completion by as much as 70%, including classless object tracking and single click smart polygon generation. Segmentation options include Keypoint, Bounding Box, Polyline, & Polygon segmentation, for image and video. Semantic Segmentation tools deliver seamless entity boundaries with pixel perfect accuracy. NLP and NER capabilities support text and audio classification and sentiment analysis. The platform is highly configurable to support hybrid use cases. Available via SaaS (Alegion Control), Managed Platform, and Managed Labeling Services.

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.

Mesh influences the accuracy, convergence and speed of a simulation. Ansys provides tools to produce the most appropriate mesh for accurate, efficient solutions. Ansys provides general purpose, high-performance, automated, intelligent meshing software that produces the most appropriate mesh for accurate, efficient multiphysics solutions — from easy, automatic meshing to highly crafted mesh. Smart defaults are built into the software to make meshing a painless and intuitive task, delivering the required resolution to capture solution gradients properly for dependable results. Ansys meshing solutions range from easy, automated meshing to highly crafted meshing. Methods available cover the meshing spectrum of high-order to linear elements and fast tetrahedral and polyhedral to high-quality hexahedral and mosaic. Ansys meshing capabilities help reduce the amount of time and effort spent to get to accurate results.

NVIDIA Picasso is a cloud service for building generative AI–powered visual applications. Enterprises, software creators, and service providers can run inference on their models, train NVIDIA Edify foundation models on proprietary data, or start from pre-trained models to generate image, video, and 3D content from text prompts. Picasso service is fully optimized for GPUs and streamlines training, optimization, and inference on NVIDIA DGX Cloud. Organizations and developers can train NVIDIA’s Edify models on their proprietary data or get started with models pre-trained with our premier partners. Expert denoising network to generate photorealistic 4K images. Temporal layers and novel video denoiser generate high-fidelity videos with temporal consistency. A novel optimization framework for generating 3D objects and meshes with high-quality geometry. Cloud service for building and deploying generative AI-powered image, video, and 3D applications.

Quarkus tailors your application for GraalVM and HotSpot. Amazingly fast boot time, incredibly low RSS memory (not just heap size!) offering near-instant scale up and high-density memory utilization in container orchestration platforms like Kubernetes. We use a technique we call compile time boot. Quarkus provides a cohesive, fun-to-use, full-stack framework by leveraging a growing list of over fifty best-of-breed libraries that you love and use. A cohesive platform for optimized developer joy with unified configuration and no hassle native executable generation. Zero configs, live reload in the blink of an eye, and streamlined code for the 80% common usages, flexible for the remainder 20%. The combination of Quarkus and Kubernetes provides an ideal environment for creating scalable, fast, and lightweight applications. Quarkus significantly increases developer productivity with tooling, pre-built integrations, application services, and more.

Kombai is a new ensemble model that can understand and code UI designs like humans. You can prompt it with design files in Figma to get high-quality React and HTML + CSS (vanilla/ tailwind) code in just a single click per component. Kombai’s proprietary ensemble model is able to “look at” complex, real-world designs, derive these inferences as a developer would, and generate code using that “understanding.”

Options for every business to train deep learning and machine learning models cost-effectively. AI accelerators for every use case, from low-cost inference to high-performance training. Simple to get started with a range of services for development and deployment. Tensor Processing Units (TPUs) are custom-built ASIC to train and execute deep neural networks. Train and run more powerful and accurate models cost-effectively with faster speed and scale. A range of NVIDIA GPUs to help with cost-effective inference or scale-up or scale-out training. Leverage RAPID and Spark with GPUs to execute deep learning. Run GPU workloads on Google Cloud where you have access to industry-leading storage, networking, and data analytics technologies. Access CPU platforms when you start a VM instance on Compute Engine. Compute Engine offers a range of both Intel and AMD processors for your VMs.

F5 Aspen Mesh empowers companies to drive more performance from their modern app environment by leveraging the power of their service mesh. As part of F5, Aspen Mesh is focused on delivering enterprise-class products that enhance companies’ modern app environments. Deliver new and differentiating features faster with microservices. Aspen Mesh lets you do that at scale, with confidence. Reduce the risk of downtime and improve your customers’ experience. If you’re scaling microservices to production on Kubernetes, Aspen Mesh will help you get the most out of your distributed systems. Aspen Mesh empowers companies to drive more performance from their modern app environment by leveraging the power of their service mesh. Alerts that decrease the risk of application failure or performance degradation based on data and machine learning models. Secure Ingress safely exposes enterprise apps to customers and the web.

Fireworks partners with the world's leading generative AI researchers to serve the best models, at the fastest speeds. Independently benchmarked to have the top speed of all inference providers. Use powerful models curated by Fireworks or our in-house trained multi-modal and function-calling models. Fireworks is the 2nd most used open-source model provider and also generates over 1M images/day. Our OpenAI-compatible API makes it easy to start building with Fireworks. Get dedicated deployments for your models to ensure uptime and speed. Fireworks is proudly compliant with HIPAA and SOC2 and offers secure VPC and VPN connectivity. Meet your needs with data privacy - own your data and your models. Serverless models are hosted by Fireworks, there's no need to configure hardware or deploy models. Fireworks.ai is a lightning-fast inference platform that helps you serve generative AI models.

With ready access to the richest flexible semantic layer, explainable AI, and reusable data modeling, data engineers and scientists can be 95% more productive — create and expand semantic data models, understand any data interrelationship, and run federated queries to speed time to insight. Stardog offers the most advanced graph data virtualization and high-performance graph database — up to 57x better price/performance — to connect any data lakehouse, warehouse or enterprise data source without moving or copying data. Scale use cases and users at lower infrastructure cost. Stardog’s inference engine intelligently applies expert knowledge dynamically at query time to uncover hidden patterns or unexpected insights in relationships that enable better data-informed decisions and business outcomes.

NCS 5700 line cards and routers bring scalability and flexibility to provider networks. Integrated Segment Routing supports performance-based service offerings and high-density 400G ports provide long-term network growth. Scale with demand with flexible port configurations from 10G to 400G and available 3.6, 4.8, 7.2 or 9.6 Tbps per slot line cards. Converge all services onto a single infrastructure and use Segment Routing for end-to-end granular traffic control that delivers the best client experience. With backward compatibility, a flexible pay-as-you-grow model, and IOS XR throughout the network, this platform offers long-term growth that scales with demand and protects investment. Power efficiency and scalability with a carrier-grade network operating system to rightsize the network footprint and lower your carbon impact.

Automated post-processing such as ‘hot-spot-extraction’ reduces several hours of post-processing time to a matter of minutes. Very effective design review is now possible with DEP MeshWorks with all the hot-spots unionized in one single model and facilitates subsequent design improvements to make ‘hot-spots’ go away. Weight optimization on the Yoke component of a construction equipment using DEP MeshWorks. With the patented Auto-parametrization technology the meshed models in DEP MeshWorks automatically become parametric CAE models enabling subsequent fast design changes. The Associative Modeler in DEP MeshWorks rapidly updates CAE models as CAD changes, dramatically reducing time for model updates. Morphing and scaling approach for generating standard and non standard percentile human Body FE models.

Network isolation with sandboxed containers and virtual private cloud (VPC) ensures the security of application runtimes. SAE provides high availability solutions for large-scale events that require precise capacity handling, high scalability, and service throttling and degradation. Fully-managed IaaS with Kubernetes clusters provide low-cost solutions for your business. SAE scales within seconds and improves the efficiency of runtimes and Java application startup. One-Stop PaaS with seamlessly integrated basic services, microservices, and DevOps products. SAE provides full-lifecycle application management. You can implement different release policies, such as phased release and canary release. The traffic-ratio-based canary release model is also supported. The release process is fully observable and can be rolled back.

Groq is on a mission to set the standard for GenAI inference speed, helping real-time AI applications come to life today. An LPU inference engine, with LPU standing for Language Processing Unit, is a new type of end-to-end processing unit system that provides the fastest inference for computationally intensive applications with a sequential component, such as AI language applications (LLMs). The LPU is designed to overcome the two LLM bottlenecks, compute density and memory bandwidth. An LPU has greater computing capacity than a GPU and CPU in regards to LLMs. This reduces the amount of time per word calculated, allowing sequences of text to be generated much faster. Additionally, eliminating external memory bottlenecks enables the LPU inference engine to deliver orders of magnitude better performance on LLMs compared to GPUs. Groq supports standard machine learning frameworks such as PyTorch, TensorFlow, and ONNX for inference.

Fast and accurate AI models suited for production. Highly-available inference API leveraging the most advanced NVIDIA GPUs. We selected the best open-source natural language processing (NLP) models from the community and deployed them for you. Fine-tune your own models - including GPT-J - or upload your in-house custom models, and deploy them easily to production. Upload or Train/Fine-Tune your own AI models - including GPT-J - from your dashboard, and use them straight away in production without worrying about deployment considerations like RAM usage, high-availability, scalability... You can upload and deploy as many models as you want to production.

These routers have a rugged industrial hardware design and a highly resilient architecture. They increase the uptime of communications networks and grid availability to help ensure message delivery. Choose from multiple platforms. Built to withstand harsh environments, the IR510 model provides enterprise-class RF mesh connectivity to Ethernet- and serial-enabled IoT devices like recloser controls, cap bank controls, and voltage regulator controls. The ruggedized IR529 model platforms provide range extension functionality to enhance the RF mesh reliability by adding paths and nodes. They also enable connectivity in low-end point density deployments.

Describe all of your cloud native infrastructure and manage as a pattern. Design your service mesh configuration and workload deployments. Apply intelligent canary strategies and performance profiles with service mesh pattern management. Assess your service mesh configuration against deployment and operational best practices with Meshery's configuration validator. Validate your service mesh's conformance to Service Mesh Interface (SMI) specifications. Dynamically load and manage your own WebAssembly filters in Envoy-based service meshes. Service mesh adapters provision, configure, and manage their respective service meshes.

fal is a serverless Python runtime that lets you scale your code in the cloud with no infra management. Build real-time AI applications with lightning-fast inference (under ~120ms). Check out some of the ready-to-use models, they have simple API endpoints ready for you to start your own AI-powered applications. Ship custom model endpoints with fine-grained control over idle timeout, max concurrency, and autoscaling. Use common models such as Stable Diffusion, Background Removal, ControlNet, and more as APIs. These models are kept warm for free. (Don't pay for cold starts) Join the discussion around our product and help shape the future of AI. Automatically scale up to hundreds of GPUs and scale down back to 0 GPUs when idle. Pay by the second only when your code is running. You can start using fal on any Python project by just importing fal and wrapping existing functions with the decorator.

Dell PowerEdge C-Series servers are a family of high-density, scale-out servers designed for use in hyper-scale and high-performance computing (HPC) environments. These servers are optimized for workloads that demand significant computational power, large storage capacity, and efficient cooling. The C-Series servers offer a modular and flexible design, allowing for customization and configuration to meet the specific needs of various applications, such as big data analytics, artificial intelligence (AI), machine learning (ML), and cloud computing. Key features of the PowerEdge C-Series include support for the latest Intel or AMD processors, high memory capacity, a variety of storage options including NVMe drives, and efficient thermal management. With their combination of performance, scalability, and versatility, Dell PowerEdge C-Series servers provide organizations with the tools to handle data-intensive and compute-heavy workloads in today's dynamic IT landscape.

Dell PowerEdge R series rack servers are enterprise-grade, rack-mountable servers designed for data centers and IT environments, offering high performance, scalability, and flexibility for diverse workloads. These servers, available in 1U, 2U, and other form factors, feature powerful Intel or AMD processors, high-density memory configurations, and storage options including HDDs, SSDs, and NVMe drives. Additionally, they provide expandability via PCIe slots, integrated management tools such as iDRAC, robust security features, and energy-efficient components. Specific features vary between models within the series, which can be deployed for applications like virtualization, high-performance computing, databases, and more.

The open source AI model you can fine-tune, distill and deploy anywhere. Our latest instruction-tuned model is available in 8B, 70B and 405B versions. Using our open ecosystem, build faster with a selection of differentiated product offerings to support your use cases. Choose from real-time inference or batch inference services. Download model weights to further optimize cost per token. Adapt for your application, improve with synthetic data and deploy on-prem or in the cloud. Use Llama system components and extend the model using zero shot tool use and RAG to build agentic behaviors. Leverage 405B high quality data to improve specialized models for specific use cases.

End-to-end project, model and hosting management platform, which allows companies to convert data and algorithms into holistic, execution-ready AI-strategies. Build, train and manage models securely with ease. Create products that consume AI models from anywhere, any time. Minimize risks of AI investments, while increasing strategic flexibility. Completely automated model testing, evaluation deployment, scaling and hardware load balancing. From real-time, low-latency, high-throughput inference to batch, long-running inference. Pay-per-second-of-use model, with an SLA, and full governance, monitoring and auditing tools. Intuitive interface that acts as a unified hub for managing projects, creating and visualizing datasets, and training models via collaborative and reproducible workflows.

Lenovo dense systems deliver massive computing power in minimal space to tackle workloads like High-Performance Computing (HPC), Artificial Intelligence (AI), cloud, grid, and analytics. In our modern age, your servers should have a modern design. With our high-density servers, even the most technical simulations can be performed with gusto. These dense systems pack a punch for all your artificial intelligence, cloud, grid, and analytics needs. Designed to be scalable, our unique water-cooled systems maximize density while putting security first. Liquid cooling innovation and leading energy efficiency packed into one smart ThinkSystem. All the processing power and reliable results you need in one cool package. By utilizing superior heat removal methods compared to air, the critical components all operate at lower temperatures, delivering greater performance in a quiet, energy-efficient system.

AI/ML API: Your Gateway to 200+ AI Models Revolutionize Your Development with a Single API AI/ML API is transforming the landscape for developers and SaaS entrepreneurs worldwide. Access over 200 cutting-edge AI models through one intuitive, developer-friendly interface. 🚀 Key Features: Vast Model Library: From NLP to computer vision, including Mixtral AI, LLaMA, Stable Diffusion, and Realistic Vision. Serverless Inference: Focus on innovation, not infrastructure management. Simple Integration: RESTful APIs and SDKs for seamless incorporation into any tech stack. Customization Options: Fine-tune models to fit your specific use cases. OpenAI API Compatible: Easy transition for existing OpenAI users. 💡 Benefits: Accelerated Development: Deploy AI features in hours, not months. Cost-Effective: GPT-4 level accuracy at 80% less cost. Scalability: From prototypes to enterprise solutions, grow without limits. 24/7 AI Solution: Reliable, always-on service for global

The only consumer privacy and identity platform built for agility in the digital age. Let us take work off your plate. We'll streamline platform integration, program rollout, and customer communication. The robust and feature-rich APIs we develop in-house are the same we give to our development partners and are fully supported by the IDX team. Every day we provide flexible solutions for our clients with an industry-first advanced cloud-native platform. Utilizing the latest in microservices architecture we deliver an easy-to-use, highly scalable, and secure environment. Platform load-balancing and auto-scaling capabilities enable us to meet high availability standards. Delivering exceptional data integrity with virtually no downtime. Built to meet the rigorous demands of Fortune 500 companies and the highest levels of government, our flexible, scalable solutions are trusted by organizations and their advisors across healthcare, commercial enterprise, financial, and higher education.

Exafunction optimizes your deep learning inference workload, delivering up to a 10x improvement in resource utilization and cost. Focus on building your deep learning application, not on managing clusters and fine-tuning performance. In most deep learning applications, CPU, I/O, and network bottlenecks lead to poor utilization of GPU hardware. Exafunction moves any GPU code to highly utilized remote resources, even spot instances. Your core logic remains an inexpensive CPU instance. Exafunction is battle-tested on applications like large-scale autonomous vehicle simulation. These workloads have complex custom models, require numerical reproducibility, and use thousands of GPUs concurrently. Exafunction supports models from major deep learning frameworks and inference runtimes. Models and dependencies like custom operators are versioned so you can always be confident you’re getting the right results.

Nebula allows you to deploy and scale your AI projects quickly, easily and cost-efficiently2 on highly robust, on-demand GPU infrastructure. Train and infer your models securely and easily on the Nebula cloud powered by the latest on-demand Nvidia GPUs and create and manage your containerized workloads through Nebula’s user-friendly orchestration layer. Access Nebula’s MLOps and low-code/no-code engines to build and deploy AI use cases for business teams and to deploy AI-powered applications swiftly and seamlessly with little to no coding. Choose between the Nebula containerized AI cloud, your on-prem environment, or any cloud of your choice. Build and scale AI-enabled business use-cases within a matter of weeks, not months, with the Nebula Unify platform.

Vespa is forBig Data + AI, online. At any scale, with unbeatable performance. To build production-worthy online applications that combine data and AI, you need more than point solutions: You need a platform that integrates data and compute to achieve true scalability and availability - and which does this without limiting your freedom to innovate. Only Vespa does this. Vespa is a fully featured search engine and vector database. It supports vector search (ANN), lexical search, and search in structured data, all in the same query. Users can easily build recommendation applications on Vespa. Integrated machine-learned model inference allows you to apply AI to make sense of your data in real-time. Together with Vespa's proven scaling and high availability, this empowers you to create production-ready search applications at any scale and with any combination of features.

TriggerMesh believes developers will increasingly build applications as a mesh of cloud-native functions and services from multiple cloud providers and on-premises. We believe this architecture is the best way for agile businesses to deliver effortless digital experiences. TriggerMesh is the first product that leverages Kubernetes and Knative to provide application integration across clouds and on-premises. With TriggerMesh, you can automate enterprise workflows by connecting applications, cloud services, and serverless functions. Cloud-native applications are becoming more popular. As a result, the number of functions that are hosted across disparate cloud infrastructure is proliferating. TriggerMesh breaks down cloud silos to provide true cross-cloud portability and interoperability

Catalyst is a highly scalable serverless platform that lets developers build and deploy world-class solutions without managing servers. A complete serverless development platform. Catalyst provides a variety of components that help you ship high-quality serverless solutions fast. Run code without managing servers. Debug locally and deploy at scale. Design workflows and orchestrate functions for resilient business-critical tasks. Store and serve large volumes of relational data. Secure your data with our fine-grain data store access controls. Store and retrieve images, documents, and other files at blazing speed. Train large datasets of structured data to create accurate prediction models. Scan and digitize paper documents, receipts, and any other image with our powerful optical character recognition API. Authenticate users securely with a variety of sign-in options to secure your application.

VictoriaMetrics is a fast and scalable open source time series database and monitoring solution. It's designed to be user-friendly, allowing users to build a monitoring platform without scalability issues and with minimal operational burden. VictoriaMetrics is ideal for solving use cases with large amounts of time series data for IT infrastructure, APM, Kubernetes, IoT sensors, automotive vehicles, industrial telemetry, financial data, and other enterprise-level workloads. VictoriaMetrics is powered by several components, making it the perfect solution for collecting metrics (both push and pull models), running queries, and generating alerts. With VictoriaMetrics, you can store millions of data points per second on a single instance or scale to a high-load monitoring system across multiple data centers. Plus, it's designed to store 10x more data using the same compute and storage resources as existing solutions, making it a highly efficient choice.

Deploy machine learning models at scale with more accuracy. Turn R&D into ROI with more models into production at scale, faster, with increased accuracy. Seldon reduces time-to-value so models can get to work faster. Scale with confidence and minimize risk through interpretable results and transparent model performance. Seldon Deploy reduces the time to production by providing production grade inference servers optimized for popular ML framework or custom language wrappers to fit your use cases. Seldon Core Enterprise provides access to cutting-edge, globally tested and trusted open source MLOps software with the reassurance of enterprise-level support. Seldon Core Enterprise is for organizations requiring: - Coverage across any number of ML models deployed plus unlimited users - Additional assurances for models in staging and production - Confidence that their ML model deployments are supported and protected.

Make AI a trusted part of your business. Build better, deploy faster, and audit easily with the flexibility of a cloud-native platform and the power to deploy anywhere. Easily import models and search cataloged models from across your organization. Save time by annotating data rapidly with model-in-the-loop hinting. Understand the full provenance of your data, models, workflows, and inferences. Deploy models where you need them, including for edge and IoT use cases. Getting valuable insights from your data is not just for data scientists. With Chariot’s low-code interface, meaningful collaboration can take place across teams. Train models rapidly using your organization's production data. Deploy models with one click and monitor models in production at scale.

Thinkmate’s high-density, multi-node HDX servers are the ultimate solution for your enterprise data center. In today's fast-paced and data-driven world, having a reliable and efficient server infrastructure is crucial for success. Whether you're dealing with complex cloud computing, virtualization, or big data analytics, our servers provide the performance and scalability you need to keep pace with your growing business needs. With a focus on high-density design, these servers are equipped with multiple nodes in a single chassis, maximizing your data center space while still delivering top-notch performance. We use the latest technologies, including Intel Xeon Scalable and AMD EPYC processors to ensure that your server can handle even the most demanding applications. In addition to raw performance, we understand the importance of reliability and availability, which is why our servers are equipped with redundant power and network connections.

Virtuoso Universal Server is a modern platform built on existing open standards that harnesses the power of Hyperlinks ( functioning as Super Keys ) for breaking down data silos that impede both user and enterprise ability. Using Virtuoso, you can easily generate financial profile knowledge graphs from near real time financial activity that reduce the cost and complexity associated with detecting fraudent activity patterns. Courtesy of its high-performance, secure, and scalable dbms engine, you can use intelligent reasoning and inference to harmonize fragmented identities using personally identifying attributes such as email addresses, phone numbers, social-security numbers, drivers licenses, etc. for building fraud detection solutions. Virtuoso helps you build powerful solutions applications driven by knowledge graphs derived from a variety of life sciences oriented data sources.

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.

Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Sagemaker instances or Amazon ECS tasks, to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, PyTorch and ONNX models. Inference is the process of making predictions using a trained model. In deep learning applications, inference accounts for up to 90% of total operational costs for two reasons. Firstly, standalone GPU instances are typically designed for model training - not for inference. While training jobs batch process hundreds of data samples in parallel, inference jobs usually process a single input in real time, and thus consume a small amount of GPU compute. This makes standalone GPU inference cost-inefficient. On the other hand, standalone CPU instances are not specialized for matrix operations, and thus are often too slow for deep learning inference.

Accelerate your deep learning workload. Speed your time to value with AI model training and inference. With advancements in compute, algorithm and data access, enterprises are adopting deep learning more widely to extract and scale insight through speech recognition, natural language processing and image classification. Deep learning can interpret text, images, audio and video at scale, generating patterns for recommendation engines, sentiment analysis, financial risk modeling and anomaly detection. High computational power has been required to process neural networks due to the number of layers and the volumes of data to train the networks. Furthermore, businesses are struggling to show results from deep learning experiments implemented in silos.

Today's Kubernetes environments need help in scaling, securing and observing modern cloud-native applications. Gloo Mesh, based on the industry's leading Istio service mesh, simplifies multi-cloud and multi-cluster management of service mesh for containers and virtual machines. Gloo Mesh helps platform engineering teams to reduce costs, reduce risks, and improve application agility. Gloo Mesh is a modular component of Gloo Platform. The service mesh allows for application-aware network tasks to be managed independently from the application, adding observability, security, and reliability to distributed applications. By introducing the service mesh to your applications, you can: Simplify the application layer Provide more insights into your traffic Increase the security of your application

Compute, storage, and networking are possible in high-density, multi-node servers at lower TCO and greater efficiency. High-Performance Computing (HPC), Hyper-Converged Infrastructure (HCI), edge computing, and file storage.

The Xilinx’s AI development platform for AI inference on Xilinx hardware platforms consists of optimized IP, tools, libraries, models, and example designs. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Xilinx FPGA and ACAP. Supports mainstream frameworks and the latest models capable of diverse deep learning tasks. Provides a comprehensive set of pre-optimized models that are ready to deploy on Xilinx devices. You can find the closest model and start re-training for your applications! Provides a powerful open source quantizer that supports pruned and unpruned model quantization, calibration, and fine tuning. The AI profiler provides layer by layer analysis to help with bottlenecks. The AI library offers open source high-level C++ and Python APIs for maximum portability from edge to cloud. Efficient and scalable IP cores can be customized to meet your needs of many different applications.

Models are temporary, pipelines are forever. Train, Evaluate, Deploy, Repeat. Valohai is the only MLOps platform that automates everything from data extraction to model deployment. Automate everything from data extraction to model deployment. Store every single model, experiment and artifact automatically. Deploy and monitor models in a managed Kubernetes cluster. Point to your code & data and hit run. Valohai launches workers, runs your experiments and shuts down the instances for you. Develop through notebooks, scripts or shared git projects in any language or framework. Expand endlessly through our open API. Automatically track each experiment and trace back from inference to the original training data. Everything fully auditable and shareable. Automatically track each experiment and trace back from inference to the original training data. Everything fully auditable and shareable.