Best Free ML Model Management Tools

Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.

An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.

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.

Koog is a Kotlin‑based framework for building and running AI agents entirely in idiomatic Kotlin, supporting both single‑run agents that process individual inputs and complex workflow agents with custom strategies and configurations. It features pure Kotlin implementation, seamless Model Control Protocol (MCP) integration for enhanced model management, vector embeddings for semantic search, and a flexible system for creating and extending tools that access external systems and APIs. Ready‑to‑use components address common AI engineering challenges, while intelligent history compression optimizes token usage and preserves context. A powerful streaming API enables real‑time response processing and parallel tool calls. Persistent memory allows agents to retain knowledge across sessions and between agents, and comprehensive tracing facilities provide detailed debugging and monitoring.

Gate22 is an enterprise-grade AI governance and MCP (Model Context Protocol) control platform that centralizes, secures, and observes how AI tools and agents access and use MCP servers across an organization. It lets administrators onboard, configure, and manage both external and internal MCP servers with fine-grained, function-level permissions, team-based access control, and role-based policies so that only approved tools and functions can be used by specific teams or users. Gate22 provides a unified MCP endpoint that bundles multiple MCP servers into a simplified interface with just two core functions, so developers and AI clients consume fewer tokens and avoid context overload while maintaining high accuracy and security. The admin view offers a governance dashboard to monitor usage patterns, maintain compliance, and enforce least-privilege access, while the member view gives streamlined, secure access to authorized MCP bundles.

Launch production-ready apps with the LMOps stack for monitoring, model management, and more. Replace your OpenAI or other provider APIs with the Portkey endpoint. Manage prompts, engines, parameters, and versions in Portkey. Switch, test, and upgrade models with confidence! View your app performance & user level aggregate metics to optimise usage and API costs Keep your user data secure from attacks and inadvertent exposure. Get proactive alerts when things go bad. A/B test your models in the real world and deploy the best performers. We built apps on top of LLM APIs for the past 2 and a half years and realised that while building a PoC took a weekend, taking it to production & managing it was a pain! We're building Portkey to help you succeed in deploying large language models APIs in your applications. Regardless of you trying Portkey, we're always happy to help!