Best AI Gateways for Azure Marketplace

Find and compare the best AI Gateways for Azure Marketplace in 2026

Use the comparison tool below to compare the top AI Gateways for Azure Marketplace on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Cloudflare Reviews
    Top Pick

    Cloudflare

    Cloudflare

    $20 per website
    2,002 Ratings
    See Software
    Learn More
    The Cloudflare AI Gateway functions as a comprehensive management and oversight platform for AI applications, enabling organizations to oversee costs, performance, and reliability across various AI service providers. By connecting to your AI solutions through a simple line of code, it provides a consolidated view of utilization, token consumption, and error metrics. With features such as real-time monitoring, caching, and rate limiting, it aids in curbing excessive spending while ensuring stable application performance. The AI Gateway seamlessly integrates with platforms like OpenAI, Hugging Face, Anthropic, and Workers AI, empowering teams with full control over their apps' interactions with diverse models. Its logging and analytics capabilities facilitate easy auditing, troubleshooting, and performance enhancement, promoting accountability across AI activities. With Cloudflare AI Gateway, developers can enhance the efficiency, reliability, and scalability of their AI applications.
  • 2
    Tyk Reviews

    Tyk

    Tyk Technologies

    $600/month
    1 Rating
    Tyk is an Open Source API Gateway and Management Platform that is leading in Open Source API Gateways and Management. It features an API gateway, analytics portal, dashboard, and a developer portal. Supporting REST, GraphQL, TCP and gRPC protocols We facilitate billions of transactions for thousands of innovative organisations. Tyk can be installed on-premises (Self-managed), Hybrid or fully SaaS.
  • 3
    Azure API Management Reviews
    Manage APIs seamlessly across both cloud environments and on-premises systems: Alongside Azure, implement API gateways in conjunction with APIs hosted in various cloud platforms and local servers to enhance the flow of API traffic. Ensure that you meet security and compliance standards while benefiting from a cohesive management experience and comprehensive visibility over all internal and external APIs. Accelerate your operations with integrated API management: Modern enterprises are increasingly leveraging API architectures to foster growth. Simplify your processes within hybrid and multi-cloud settings by utilizing a centralized platform for overseeing all your APIs. Safeguard your resources effectively: Choose to selectively share data and services with employees, partners, and clients by enforcing authentication, authorization, and usage restrictions to maintain control over access. By doing so, you can ensure that your systems remain secure while still allowing for collaboration and efficient interaction.
  • 4
    Dataiku Reviews
    Dataiku is a comprehensive enterprise AI platform built to transform how organizations develop, deploy, and manage artificial intelligence at scale. It unifies data, analytics, and machine learning into a centralized environment where both technical and non-technical users can collaborate effectively. The platform enables teams to design and operationalize AI workflows, from data preparation to model deployment and monitoring. With its orchestration capabilities, Dataiku connects various data systems, applications, and processes to streamline operations across the enterprise. It also offers robust governance features that ensure transparency, compliance, and cost control throughout the AI lifecycle. Organizations can build intelligent agents, automate decision-making, and enhance analytics without disrupting existing workflows. Dataiku supports the transition from siloed models to production-ready machine learning systems that can be reused and scaled. Its flexibility allows businesses to modernize legacy analytics while preserving institutional knowledge. Companies across industries leverage the platform to accelerate innovation, improve efficiency, and unlock new revenue opportunities. By combining scalability, governance, and usability, Dataiku empowers enterprises to turn AI into a strategic advantage.
  • 5
    DreamFactory Reviews

    DreamFactory

    DreamFactory Software

    $1500/month
    DreamFactory is a REST API Management Platform. Auto Generate REST APIs. A cloud-based or on-premise API generation platform that is enterprise-grade. Instantly generate database APIs to build faster applications. The biggest bottleneck in modern IT is eliminated. Your project can be launched in weeks instead of months. DreamFactory creates a secure, standardized and reusable, fully documented, live REST API. DreamFactory can integrate any SQL or NoSQL file storage system or SOAP service. It instantly creates a RESTAPI with Swagger documentation, user role, and more. Every API endpoint is secured with User Management, Role Based Access Controls, SSO Authentication and Swagger documentation. Rapidly create mobile, web and IoT apps using REST-based APIs. DreamFactory offers example apps for iOS, Android and Titanium.
  • 6
    MLflow Reviews
    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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