Alternatives to TrueFoundry

Gemini Enterprise Agent Platform is Google Cloud’s next-generation system for designing and managing advanced AI agents across the enterprise. Built as the successor to Vertex AI, it unifies model selection, development, and deployment into a single scalable environment. The platform supports a vast ecosystem of over 200 AI models, including Google’s latest Gemini innovations and popular third-party models. It offers flexible development tools like Agent Studio for visual workflows and the Agent Development Kit for deeper customization. Businesses can deploy agents that operate continuously, maintain long-term memory, and handle multi-step processes with high efficiency. Security and governance are central, with features such as agent identity verification, centralized registries, and controlled access through gateways. The platform also enables seamless integration with enterprise systems, allowing agents to interact with data, applications, and workflows securely. Advanced monitoring tools provide real-time insights into agent behavior and performance. Optimization features help refine agent logic and improve accuracy over time. By combining automation, intelligence, and governance, the platform helps organizations transition to autonomous, AI-driven operations. It ultimately supports faster innovation while maintaining enterprise-grade reliability and control.

Teradata VantageCloud: Open, Scalable Cloud Analytics for AI VantageCloud is Teradata’s cloud-native analytics and data platform designed for performance and flexibility. It unifies data from multiple sources, supports complex analytics at scale, and makes it easier to deploy AI and machine learning models in production. With built-in support for multi-cloud and hybrid deployments, VantageCloud lets organizations manage data across AWS, Azure, Google Cloud, and on-prem environments without vendor lock-in. Its open architecture integrates with modern data tools and standard formats, giving developers and data teams freedom to innovate while keeping costs predictable.

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.

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.

agentgateway is an AI-native gateway built to manage, secure, and observe modern AI and agentic systems. It acts as a centralized control plane for LLMs, AI agents, and tool servers using protocols like MCP and A2A. Designed specifically for AI workloads, agentgateway supports connectivity patterns that legacy gateways cannot. The platform provides secure LLM access, preventing data leaks, malicious prompts, and uncontrolled usage. Enterprises gain full visibility into how models, agents, and tools interact across the ecosystem. agentgateway simplifies governance with centralized policy enforcement and access control. It also enables consistent observability using standards like OpenTelemetry. As an open-source project hosted by the Linux Foundation, it promotes vendor-neutral interoperability. agentgateway helps organizations scale AI responsibly and securely. It delivers a future-ready foundation for agentic connectivity.

Cyclr is an embedded integration toolkit (embedded iPaaS) for creating, managing and publishing white-labelled integrations directly into your SaaS application. With a low-code, visual integration builder and a fully featured unified API for developers, all teams can impact integration creation and delivery. Flexible deployment methods include an in-app Embedded integration marketplace, where you can push your new integrations live, for your users to self serve, in minutes. Cyclr's fully multi-tenanted architecture helps you scale your integrations with security fully built in - you can even opt for Private deployments (managed or in your infrastructure). Accelerate your AI strategy by Creating and publishing your own MCP Servers too, so you can make your SaaS usable inside LLMs. We help take the hassle out of delivering your users' integration needs.

Deploy your machine learning model in the cloud within minutes using a consolidated packaging format that supports both online and offline operations across various platforms. Experience a performance boost with throughput that is 100 times greater than traditional flask-based model servers, achieved through our innovative micro-batching technique. Provide exceptional prediction services that align seamlessly with DevOps practices and integrate effortlessly with widely-used infrastructure tools. The unified deployment format ensures high-performance model serving while incorporating best practices for DevOps. This service utilizes the BERT model, which has been trained with the TensorFlow framework to effectively gauge the sentiment of movie reviews. Our BentoML workflow eliminates the need for DevOps expertise, automating everything from prediction service registration to deployment and endpoint monitoring, all set up effortlessly for your team. This creates a robust environment for managing substantial ML workloads in production. Ensure that all models, deployments, and updates are easily accessible and maintain control over access through SSO, RBAC, client authentication, and detailed auditing logs, thereby enhancing both security and transparency within your operations. With these features, your machine learning deployment process becomes more efficient and manageable than ever before.

Zapier is a comprehensive AI automation platform that helps organizations transform how work gets done. It allows teams to connect AI tools with everyday apps to automate workflows end to end. Zapier supports AI workflows, custom agents, chatbots, forms, and data tables in one unified system. With over 8,000 integrations, it eliminates manual handoffs between tools and teams. Built-in AI assistance helps users design automations quickly without technical complexity. Zapier enables teams to deploy AI agents that work continuously, even outside business hours. The platform offers full visibility into automation activity with audit logs and analytics. Enterprise-grade security and compliance ensure safe AI adoption at scale. Zapier is used across departments including marketing, sales, IT, and operations. It helps teams save time, reduce costs, and scale productivity with confidence.

Domino is a comprehensive enterprise AI platform that enables organizations to transform AI initiatives into scalable, production-ready systems. It supports the full AI lifecycle, including data access, model development, deployment, and ongoing management. The platform provides a self-service environment where data scientists can access tools, datasets, and compute resources with built-in governance and security controls. Domino allows teams to build machine learning models, generative AI applications, and intelligent agents using their preferred development environments. It also includes advanced orchestration capabilities to manage workloads across hybrid, multi-cloud, and on-premises infrastructures. Governance features such as model registries, audit trails, and policy enforcement ensure compliance and reproducibility. The platform enhances collaboration by providing a centralized system of record for all AI assets and experiments. Additionally, it helps organizations optimize costs through resource management and usage tracking. Domino is designed to meet enterprise standards for security and regulatory compliance. Ultimately, it empowers businesses to accelerate AI innovation while maintaining operational control and accountability.

OpenRouter serves as a consolidated interface for various large language models (LLMs). It efficiently identifies the most competitive prices and optimal latencies/throughputs from numerous providers, allowing users to establish their own priorities for these factors. There’s no need to modify your existing code when switching between different models or providers, making the process seamless. Users also have the option to select and finance their own models. Instead of relying solely on flawed evaluations, OpenRouter enables the comparison of models based on their actual usage across various applications. You can engage with multiple models simultaneously in a chatroom setting. The payment for model usage can be managed by users, developers, or a combination of both, and the availability of models may fluctuate. Additionally, you can access information about models, pricing, and limitations through an API. OpenRouter intelligently directs requests to the most suitable providers for your chosen model, in line with your specified preferences. By default, it distributes requests evenly among the leading providers to ensure maximum uptime; however, you have the flexibility to tailor this process by adjusting the provider object within the request body. Prioritizing providers that have maintained a stable performance without significant outages in the past 10 seconds is also a key feature. Ultimately, OpenRouter simplifies the process of working with multiple LLMs, making it a valuable tool for developers and users alike.

Axway Amplify is a modular API and integration platform designed to help enterprises connect systems, govern APIs, and enable secure AI-ready digital experiences. It supports federated API management, giving organizations visibility and control across APIs that live in different clouds, on-premises systems, gateways, repositories, and vendor environments. Amplify API Management helps teams design, implement, secure, publish, and manage APIs throughout the full lifecycle. Amplify Fusion provides low-code and no-code integration tools that allow business and IT users to build event-based workflows, connect applications, and automate recurring processes. Amplify Engage creates a marketplace for curated API products and digital assets, helping developers discover, subscribe to, and reuse approved APIs. Amplify AI Gateway helps organizations scale AI responsibly by protecting prompts, orchestrating LLM usage, authenticating access to AI services, and controlling compliance requirements. The platform also includes centralized monitoring, governance, and management capabilities for APIs across AWS, Azure, Istio, Axway, and other gateway environments. Amplify is modular, so companies can begin with API management, integration, AI governance, or API marketplace capabilities and expand over time. By combining API security, discovery, governance, integration, and AI enablement, Axway Amplify helps enterprises modernize without abandoning systems that already work.

The Databricks Data Intelligence Platform empowers every member of your organization to leverage data and artificial intelligence effectively. Constructed on a lakehouse architecture, it establishes a cohesive and transparent foundation for all aspects of data management and governance, enhanced by a Data Intelligence Engine that recognizes the distinct characteristics of your data. Companies that excel across various sectors will be those that harness the power of data and AI. Covering everything from ETL processes to data warehousing and generative AI, Databricks facilitates the streamlining and acceleration of your data and AI objectives. By merging generative AI with the integrative advantages of a lakehouse, Databricks fuels a Data Intelligence Engine that comprehends the specific semantics of your data. This functionality enables the platform to optimize performance automatically and manage infrastructure in a manner tailored to your organization's needs. Additionally, the Data Intelligence Engine is designed to grasp the unique language of your enterprise, making the search and exploration of new data as straightforward as posing a question to a colleague, thus fostering collaboration and efficiency. Ultimately, this innovative approach transforms the way organizations interact with their data, driving better decision-making and insights.

JFrog ML (formerly Qwak) is a comprehensive MLOps platform that provides end-to-end management for building, training, and deploying AI models. The platform supports large-scale AI applications, including LLMs, and offers capabilities like automatic model retraining, real-time performance monitoring, and scalable deployment options. It also provides a centralized feature store for managing the entire feature lifecycle, as well as tools for ingesting, processing, and transforming data from multiple sources. JFrog ML is built to enable fast experimentation, collaboration, and deployment across various AI and ML use cases, making it an ideal platform for organizations looking to streamline their AI workflows.

Storm MCP serves as an advanced gateway centered on the Model Context Protocol (MCP), facilitating seamless connections between AI applications and multiple verified MCP servers through a straightforward one-click deployment process. It ensures robust enterprise-level security, enhanced observability, and easy integration of tools without the need for extensive custom development. By standardizing AI connections and only exposing specific tools from each MCP server, it helps minimize token consumption and optimizes the selection of model tools. With its Lightning deployment feature, users can access over 30 secure MCP servers, while Storm efficiently manages OAuth-based access, comprehensive usage logs, rate limitations, and monitoring. This innovative solution is crafted to connect AI agents to external context sources securely, allowing developers to sidestep the complexities of building and maintaining their own MCP servers. Tailored for AI agent developers, workflow creators, and independent innovators, Storm MCP stands out as a flexible and configurable API gateway, simplifying infrastructure challenges while delivering dependable context for diverse applications. Its unique capabilities make it an essential tool for those looking to enhance their AI integration experience.

Solo Enterprise offers a comprehensive cloud-native application networking and connectivity solution that enables businesses to securely connect, scale, manage, and monitor APIs, microservices, and advanced AI workloads within distributed infrastructures, particularly in Kubernetes-based and multi-cluster environments. The platform's foundational features leverage open-source technologies such as Envoy and Istio, including Gloo Gateway, which facilitates omnidirectional API management by effectively handling external, internal, and third-party traffic while ensuring security, authentication, traffic routing, observability, and analytics. Additionally, Gloo Mesh provides a centralized control mechanism for multi-cluster service mesh, streamlining service-to-service connectivity and security across different clusters. Moreover, the Agentgateway and Gloo AI Gateway enable secure and governed traffic for LLM/AI agents, incorporating essential guardrails and integration capabilities to enhance functionality and security. This multifaceted approach ensures that enterprises can operate efficiently in a rapidly evolving technological landscape.

Webrix MCP Gateway serves as a comprehensive infrastructure for enterprises aiming to integrate AI solutions securely, allowing for seamless connections between various AI agents (such as Claude, ChatGPT, Cursor, and n8n) and internal systems on a large scale. Utilizing the Model Context Protocol standard, Webrix presents a unified secure gateway that tackles the primary hurdle hindering AI adoption: security apprehensions related to tool accessibility. Key features include: - Centralized Single Sign-On (SSO) and Role-Based Access Control (RBAC) – This allows employees to connect to authorized tools immediately, bypassing the need for IT ticket requests. - Universal agent compatibility – The platform supports any AI agent that complies with the MCP standard. - Robust enterprise security – Encompasses audit logs, credential management, and strict policy enforcement. - Self-service functionality – Employees can effortlessly access internal resources (like Jira, GitHub, databases, and APIs) through their chosen AI agents without requiring manual setups. By addressing the essential challenge of AI integration, Webrix empowers your workforce with the necessary AI capabilities while ensuring robust security, oversight, and compliance. Whether you choose to deploy it on-premise, within your cloud infrastructure, or utilize our managed services, Webrix adapts to fit your organization's needs.

LLM Gateway is a completely open-source, unified API gateway designed to efficiently route, manage, and analyze requests directed to various large language model providers such as OpenAI, Anthropic, and Gemini Enterprise Agent Platform, all through a single, OpenAI-compatible endpoint. It supports multiple providers, facilitating effortless migration and integration, while its dynamic model orchestration directs each request to the most suitable engine, providing a streamlined experience. Additionally, it includes robust usage analytics that allow users to monitor requests, token usage, response times, and costs in real-time, ensuring transparency and control. The platform features built-in performance monitoring tools that facilitate the comparison of models based on accuracy and cost-effectiveness, while secure key management consolidates API credentials under a role-based access framework. Users have the flexibility to deploy LLM Gateway on their own infrastructure under the MIT license or utilize the hosted service as a progressive web app, with easy integration that requires only a change to the API base URL, ensuring that existing code in any programming language or framework, such as cURL, Python, TypeScript, or Go, remains functional without any alterations. Overall, LLM Gateway empowers developers with a versatile and efficient tool for leveraging various AI models while maintaining control over their usage and expenses.

Bifrost serves as a powerful AI gateway that consolidates access to over 20 providers, including OpenAI, Anthropic, AWS, Bedrock, Google Vertex, Azure, and others, all via a single API. It allows for rapid deployment in mere seconds without the need for any configuration, ensuring features such as automatic failover, load balancing, semantic caching, and robust enterprise governance. In rigorous tests handling 5,000 requests per second, Bifrost introduces a minimal overhead of just 11 microseconds for each request, showcasing its efficiency and reliability for high-demand applications. This makes it an ideal choice for organizations looking to streamline their AI integrations while maintaining performance.

TensorBlock is an innovative open-source AI infrastructure platform aimed at making large language models accessible to everyone through two interrelated components. Its primary product, Forge, serves as a self-hosted API gateway that prioritizes privacy while consolidating connections to various LLM providers into a single endpoint compatible with OpenAI, incorporating features like encrypted key management, adaptive model routing, usage analytics, and cost-efficient orchestration. In tandem with Forge, TensorBlock Studio provides a streamlined, developer-friendly workspace for interacting with multiple LLMs, offering a plugin-based user interface, customizable prompt workflows, real-time chat history, and integrated natural language APIs that facilitate prompt engineering and model evaluations. Designed with a modular and scalable framework, TensorBlock is driven by ideals of transparency, interoperability, and equity, empowering organizations to explore, deploy, and oversee AI agents while maintaining comprehensive control and reducing infrastructure burdens. This dual approach ensures that users can effectively leverage AI capabilities without being hindered by technical complexities or excessive costs.

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.

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.

Microsoft Foundry provides a unified environment for building AI-powered applications and agents that reflect your organization’s knowledge, workflows, and security standards. Developers can tap into more than 11,000 cutting-edge models, instantly benchmark them, and route intelligently for real-time performance gains. The platform simplifies development with a consistent API, prebuilt SDKs, and solution templates that accelerate integration with existing systems. Foundry also incorporates enterprise-grade governance, providing centralized monitoring, compliance controls, and secure model operations across all teams. Organizations can embed AI directly into tools they already use — such as GitHub, Visual Studio, and Fabric — to streamline development. Its interoperability with cloud infrastructure and business data ensures every model is grounded, accurate, and production-ready. From automating internal workflows to powering transformative customer experiences, Foundry enables high-impact AI at scale. By combining model breadth, developer velocity, and enterprise security, Microsoft Foundry delivers an unmatched foundation for modern AI innovation.

Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500 companies, such as United, Kroger, Philips, Truist, and many others.

FastRouter serves as a comprehensive API gateway designed to facilitate AI applications in accessing a variety of large language, image, and audio models (such as GPT-5, Claude 4 Opus, Gemini 2.5 Pro, and Grok 4) through a streamlined OpenAI-compatible endpoint. Its automatic routing capabilities intelligently select the best model for each request by considering important factors like cost, latency, and output quality, ensuring optimal performance. Additionally, FastRouter is built to handle extensive workloads without any imposed query per second limits, guaranteeing high availability through immediate failover options among different model providers. The platform also incorporates robust cost management and governance functionalities, allowing users to establish budgets, enforce rate limits, and designate model permissions for each API key or project. Real-time analytics are provided, offering insights into token utilization, request frequencies, and spending patterns. Furthermore, the integration process is remarkably straightforward; users simply need to replace their OpenAI base URL with FastRouter’s endpoint while configuring their preferences in the user-friendly dashboard, allowing the routing, optimization, and failover processes to operate seamlessly in the background. This ease of use, combined with powerful features, makes FastRouter an indispensable tool for developers seeking to maximize the efficiency of their AI applications.

Kong AI Gateway serves as a sophisticated semantic AI gateway that manages and secures traffic from Large Language Models (LLMs), facilitating the rapid integration of Generative AI (GenAI) through innovative semantic AI plugins. This platform empowers users to seamlessly integrate, secure, and monitor widely-used LLMs while enhancing AI interactions with features like semantic caching and robust security protocols. Additionally, it introduces advanced prompt engineering techniques to ensure compliance and governance are maintained. Developers benefit from the simplicity of adapting their existing AI applications with just a single line of code, which significantly streamlines the migration process. Furthermore, Kong AI Gateway provides no-code AI integrations, enabling users to transform and enrich API responses effortlessly through declarative configurations. By establishing advanced prompt security measures, it determines acceptable behaviors and facilitates the creation of optimized prompts using AI templates that are compatible with OpenAI's interface. This powerful combination of features positions Kong AI Gateway as an essential tool for organizations looking to harness the full potential of AI technology.

Dagster is the cloud-native open-source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. It is the platform of choice data teams responsible for the development, production, and observation of data assets. With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early.

H2O.ai stands at the forefront of open source AI and machine learning, dedicated to making artificial intelligence accessible to all. Our cutting-edge platforms, which are designed for enterprise readiness, support hundreds of thousands of data scientists across more than 20,000 organizations worldwide. By enabling companies in sectors such as finance, insurance, healthcare, telecommunications, retail, pharmaceuticals, and marketing, we are helping to foster a new wave of businesses that harness the power of AI to drive tangible value and innovation in today's marketplace. With our commitment to democratizing technology, we aim to transform how industries operate and thrive.

Vercel AI Gateway is a centralized AI model routing and infrastructure platform designed to help developers build, deploy, and scale AI-powered applications using a single unified interface for multiple AI providers and models. The platform enables developers to access text, image, and video generation models from leading AI labs including OpenAI, Anthropic, xAI, and other providers through one API endpoint, one authentication layer, and one management dashboard. AI Gateway simplifies AI application development by consolidating model routing, usage monitoring, billing, failover management, and observability into a single system, eliminating the need to integrate separately with multiple AI vendors. Developers can use the Vercel AI SDK or OpenAI-compatible APIs to build AI applications with support for streaming responses, stateful agents, multimodal generation, tool calling, and conversational workflows. The platform includes built-in resiliency features such as automatic provider failovers and workload routing to maintain uptime during outages or degraded model performance. AI Gateway also provides unified cost tracking and transparent billing with no markup over provider pricing, helping teams monitor AI usage across applications and providers more effectively. In addition to text generation, the platform supports image generation and editing workflows, as well as production-ready AI video generation capabilities accessible through prompt-based interfaces. Integrated developer tooling, SDKs for multiple programming languages, authentication management, and deployment workflows make Vercel AI Gateway particularly suited for modern web applications, AI agents, SaaS platforms, and developer-focused AI products.

nexos.ai, a powerful model-gateway, delivers AI solutions that are game-changing. Using intelligent decision-making and advanced automation, nexos.ai simplifies operations, boosts productivity, and accelerates business growth.

Orq.ai stands out as the leading platform tailored for software teams to effectively manage agentic AI systems on a large scale. It allows you to refine prompts, implement various use cases, and track performance meticulously, ensuring no blind spots and eliminating the need for vibe checks. Users can test different prompts and LLM settings prior to launching them into production. Furthermore, it provides the capability to assess agentic AI systems within offline environments. The platform enables the deployment of GenAI features to designated user groups, all while maintaining robust guardrails, prioritizing data privacy, and utilizing advanced RAG pipelines. It also offers the ability to visualize all agent-triggered events, facilitating rapid debugging. Users gain detailed oversight of costs, latency, and overall performance. Additionally, you can connect with your preferred AI models or even integrate your own. Orq.ai accelerates workflow efficiency with readily available components specifically designed for agentic AI systems. It centralizes the management of essential phases in the LLM application lifecycle within a single platform. With options for self-hosted or hybrid deployment, it ensures compliance with SOC 2 and GDPR standards, thereby providing enterprise-level security. This comprehensive approach not only streamlines operations but also empowers teams to innovate and adapt swiftly in a dynamic technological landscape.

LiteLLM serves as a comprehensive platform that simplifies engagement with more than 100 Large Language Models (LLMs) via a single, cohesive interface. It includes both a Proxy Server (LLM Gateway) and a Python SDK, which allow developers to effectively incorporate a variety of LLMs into their applications without hassle. The Proxy Server provides a centralized approach to management, enabling load balancing, monitoring costs across different projects, and ensuring that input/output formats align with OpenAI standards. Supporting a wide range of providers, this system enhances operational oversight by creating distinct call IDs for each request, which is essential for accurate tracking and logging within various systems. Additionally, developers can utilize pre-configured callbacks to log information with different tools, further enhancing functionality. For enterprise clients, LiteLLM presents a suite of sophisticated features, including Single Sign-On (SSO), comprehensive user management, and dedicated support channels such as Discord and Slack, ensuring that businesses have the resources they need to thrive. This holistic approach not only improves efficiency but also fosters a collaborative environment where innovation can flourish.

OrcaRouter serves as a routing system for AI models that are compatible with OpenAI, efficiently directing prompts to the appropriate models from a wide array, including OpenAI, Anthropic, Gemini, DeepSeek, Qwen, Kimi, and over 200 other leading and open-source models. Its design aims to maintain the high quality of responses while minimizing costs associated with AI inference by evaluating each prompt and directing complex reasoning tasks to premium models while assigning simpler tasks to more economical open-source options. The routing process is meticulously quality-graded, avoiding arbitrary swaps for cheaper models, and every request clearly indicates the difficulty rating, chosen model, provider, and associated costs, ensuring that routes remain transparent, accountable, and reproducible. Developers can easily switch models by updating the API base URL, while previously established SDKs, model names, and streaming functionalities remain operational. Additionally, OrcaRouter features seamless automatic failover capabilities, allowing for traffic rerouting without interruption should a provider experience downtime, thus preventing disruptions for users. It also offers comprehensive API key management that incorporates spending limits, model allowlists, rate restrictions, and budget compliance, among other functionalities, ensuring robust control over resource usage. This combination of features makes OrcaRouter an indispensable tool for optimizing AI model utilization in various applications.

Effortlessly manage, process, and transform CAD, FE, CFD, and test data with ease. Establish automatic data pipelines for machine learning, reduced order modeling, and 3D deep learning applications. Eliminate the complexity of data science without the need for coding. Key Ward's platform stands out as the pioneering end-to-end no-code engineering solution, fundamentally changing the way engineers work with their data, whether it be experimental or CAx. By harnessing the power of engineering data intelligence, our software empowers engineers to seamlessly navigate their multi-source data, extracting immediate value through integrated advanced analytics tools while also allowing for the custom development of machine learning and deep learning models, all within a single platform with just a few clicks. Centralize, update, extract, sort, clean, and prepare your diverse data sources for thorough analysis, machine learning, or deep learning applications automatically. Additionally, leverage our sophisticated analytics tools on your experimental and simulation data to uncover correlations, discover dependencies, and reveal underlying patterns that can drive innovation in engineering processes. Ultimately, this approach streamlines workflows, enhancing productivity and enabling more informed decision-making in engineering endeavors.

All the essential tools for improving your business decisions are at your fingertips. The Fosfor Decision Cloud integrates the contemporary data ecosystem, fulfilling the long-awaited potential of AI by driving superior business results. By consolidating the elements of your data architecture into an innovative decision stack, the Fosfor Decision Cloud is designed to elevate business performance. Fosfor collaborates effortlessly with its partners to establish a cutting-edge decision stack that unlocks exceptional value from your data investments, ensuring that you can make informed choices with confidence. This collaborative approach not only enhances decision-making but also fosters a culture of data-driven success.

Created by LM-SYS, RouteLLM is a publicly available toolkit that enables users to direct tasks among various large language models to enhance resource management and efficiency. It features strategy-driven routing, which assists developers in optimizing speed, precision, and expenses by dynamically choosing the most suitable model for each specific input. This innovative approach not only streamlines workflows but also enhances the overall performance of language model applications.

SAS Viya is an advanced cloud-native data and AI platform designed to help organizations manage data, develop AI models, and operationalize analytics from one unified environment. The platform combines data access, machine learning, analytics, governance, and decision deployment into a scalable system built for enterprise use. SAS Viya enables businesses to connect to data across multiple sources while maintaining transparency, lineage, governance, and auditability throughout the AI lifecycle. Organizations can use the platform to accelerate model development, streamline workflows, and deploy trusted AI solutions faster and more efficiently. The platform includes built-in governance features that support fairness, explainability, compliance, and responsible AI practices across teams and business processes. SAS Viya also supports secure AI agent integration through the SAS Viya MCP Server, allowing AI-driven tools and copilots to interact with enterprise workflows responsibly. Businesses can deploy the platform in cloud, hybrid, or on-premises environments based on operational and security requirements. SAS Viya is used across industries for applications such as fraud detection, healthcare analytics, forecasting, customer intelligence, and AI model operationalization. The platform is designed to improve productivity by simplifying complex AI workflows and enabling collaboration between data scientists, analysts, and business users. Backed by decades of analytics expertise, SAS Viya helps organizations transform raw data into transparent and actionable business decisions at scale.

WSO2 Devant is an integration platform designed with AI at its core, enabling businesses to seamlessly connect, integrate, and create intelligent applications across various systems, data sources, and AI services in the modern technological landscape. This platform facilitates connections to generative AI models, vector databases, and AI agents, enriching applications with advanced AI features while addressing complex integration challenges with ease. Devant offers both no-code/low-code and pro-code development experiences, enhanced by AI tools that assist in tasks such as natural-language-based code generation, suggestions, automated data mapping, and testing, all aimed at accelerating integration workflows and improving collaboration between business and IT teams. Furthermore, it boasts a comprehensive library of connectors and templates, allowing users to orchestrate integrations across multiple protocols including REST, GraphQL, gRPC, WebSockets, and TCP, while also ensuring scalability across hybrid and multi-cloud environments, effectively bridging systems, databases, and AI agents for optimal performance. This innovative platform not only streamlines integration processes but also empowers organizations to harness the full potential of AI in their operations.

Zerve is the agentic data workspace designed for anyone who works with data, from solo analysts, data scientists and business users alike. Zerve brings together exploration, advanced analysis, collaboration, and production deployment into a single AI-native environment, so that important data work doesn’t stall, break, or disappear. Zerve is used by data professionals in companies such as BBC, QVC, Dun & Bradstreet, Airbus, and many others. Zerve makes advanced data work accessible, durable, and deployable from day one, starting with the messy, real-world data most projects begin with. At the heart of Zerve is a new way for humans and AI agents to work together. Zerve’s AI agents understand the full context of a project and actively help plan, build, debug, and iterate across multi-step analyses. Agents can assist with tasks like cleaning and transforming data, identifying issues, and testing approaches, reducing the manual effort that slows teams down. This means working at a higher level of abstraction without being slowed by setup or syntax. With Zerve, you always have an expert data scientist at your side, guiding decisions, suggesting next steps, and taking action. Unlike traditional data notebooks, workflows in Zerve are reproducible and stable. Users can work across Python, SQL, and R in a single workspace, connect directly to databases, data lakes, and warehouses, and integrate with Git for version control. The built-in distributed computing engine powers massively parallel execution for large-scale analysis, simulations, and AI workloads, with multi-agent orchestration coordinating complex pipelines behind the scenes. Zerve can be used as SaaS, self-hosted, or even on-premise for regulated environments.

One platform to build, integrate, and expose your digital services as managed APIs in cloud, on-premises and hybrid architectures to support your digital transformation strategy. Integrate with your existing identity access and key management tools to implement industry-standard authorization flows, such as OAuth Connect, OpenID Connect, or JWTs. You can create APIs using existing services, manage APIs both from third-party providers and internally built applications, and monitor their usage, performance, and retirement. To optimize your developer support, improve your services and drive adoption, you can provide real-time access API usage and performance statistics for decision-makers.

BDB is an advanced platform for data analytics and business intelligence that excels in extracting valuable insights from your data. It can be implemented both in cloud environments and on-premises. With a unique microservices architecture, it incorporates components for Data Preparation, Predictive Analytics, Pipelines, and Dashboard design, enabling tailored solutions and scalable analytics across various sectors. Thanks to its robust NLP-driven search functionality, users can harness the potential of data seamlessly across desktops, tablets, and mobile devices. BDB offers numerous integrated data connectors, allowing it to interface with a wide array of popular data sources, applications, third-party APIs, IoT devices, and social media platforms in real-time. It facilitates connections to relational databases, big data systems, FTP/SFTP servers, flat files, and web services, effectively managing structured, semi-structured, and unstructured data. Embark on your path to cutting-edge analytics today, and discover the transformative power of BDB for your organization.

LangDB provides a collaborative, open-access database dedicated to various natural language processing tasks and datasets across multiple languages. This platform acts as a primary hub for monitoring benchmarks, distributing tools, and fostering the advancement of multilingual AI models, prioritizing transparency and inclusivity in linguistic representation. Its community-oriented approach encourages contributions from users worldwide, enhancing the richness of the available resources.

Factory Router is an automated model-selection system tailored for autonomous software engineering workflows, aiming to achieve top-tier performance while minimizing costs and enhancing reliability. Rather than relying on engineers to manually identify the optimal model for each task, Factory Router intelligently selects the appropriate model for each Droid session from a varied collection of advanced and efficient models. Routine tasks such as answering simple queries, executing mechanical refactors, making documentation updates, addressing minor bugs, and conducting search-intensive investigations can be efficiently managed by the more streamlined models, whereas complex assignments that require in-depth reasoning can be assigned to the cutting-edge models. Should the chosen model encounter difficulties in completing a task, Factory Router has the capability to transition the session to a more proficient model, ensuring a consistent standard of quality in outcomes. Additionally, it adeptly navigates across different models, providers, and resource capacities whenever issues arise, such as endpoint degradation, rate limits being reached, or limited capacity, thus ensuring uninterrupted operation of Droid sessions. This innovative approach not only enhances productivity but also significantly reduces the burden on engineers, allowing them to focus on more strategic initiatives.

Amazon SageMaker Unified Studio provides a seamless and integrated environment for data teams to manage AI and machine learning projects from start to finish. It combines the power of AWS’s analytics tools—like Amazon Athena, Redshift, and Glue—with machine learning workflows, enabling users to build, train, and deploy models more effectively. The platform supports collaborative project work, secure data sharing, and access to Amazon’s AI services for generative AI app development. With built-in tools for model training, inference, and evaluation, SageMaker Unified Studio accelerates the AI development lifecycle.

LMOps is a stack that allows you to launch production-ready applications for monitoring, model management and more. Portkey is a replacement for OpenAI or any other provider APIs. Portkey allows you to manage engines, parameters and versions. Switch, upgrade, and test models with confidence. View aggregate metrics for your app and users to optimize usage and API costs Protect your user data from malicious attacks and accidental exposure. Receive proactive alerts if things go wrong. Test your models in real-world conditions and deploy the best performers. We have been building apps on top of LLM's APIs for over 2 1/2 years. While building a PoC only took a weekend, bringing it to production and managing it was a hassle! We built Portkey to help you successfully deploy large language models APIs into your applications. We're happy to help you, regardless of whether or not you try Portkey!

ModelArts, an all-encompassing AI development platform from Huawei Cloud, is crafted to optimize the complete AI workflow for both developers and data scientists. This platform encompasses a comprehensive toolchain that facilitates various phases of AI development, including data preprocessing, semi-automated data labeling, distributed training, automated model creation, and versatile deployment across cloud, edge, and on-premises systems. It is compatible with widely used open-source AI frameworks such as TensorFlow, PyTorch, and MindSpore, while also enabling the integration of customized algorithms to meet unique project requirements. The platform's end-to-end development pipeline fosters enhanced collaboration among DataOps, MLOps, and DevOps teams, resulting in improved development efficiency by as much as 50%. Furthermore, ModelArts offers budget-friendly AI computing resources with a range of specifications, supporting extensive distributed training and accelerating inference processes. This flexibility empowers organizations to adapt their AI solutions to meet evolving business challenges effectively.