Introducing AgentOpera AI App, the Generalized AI Agent, and AgentOpera Framework and Platform Behind It

We are very excited to share with our customers and friends that TensorOpera AI (formally FedML) is now officially an AI Agent and Model company, focused on building production-grade vertical AI solutions with our agentic AI platform. This is a big step forward—and today, we introduce the AgentOpera AI App, our Generalized AI Agent (https://chat.tensoropera.ai), and the powerful AgentOpera Framework and Platform that makes it all possible.

AgentOpera AI: Generalized AI Agent App

On the application layer, we introduce the AgentOpera AI App—an intuitive gateway into the world of generalized AI agents. End users can engage in ChatGPT-like conversations, enhanced with deep research capabilities, real-time web search, and access to a diverse set of proprietary and open-source foundation models. Behind the scenes, the AgentOpera AI App is powered by a dynamic agent network, intelligently routing user prompts to the most suitable agents—or even orchestrating multiple agents to collaboratively complete complex workflows.

Our vision goes beyond standalone tools. We’re building an ecosystem where diverse models, MCP servers (tools), and agent services can plug into a shared, interoperable network. This method allows us to grow collaboratively with the community, accelerating innovation and utility for all.

AgentOpera Framework: Evolving Toward Agentic OS and Networks

At the heart of our architecture is the AgentOpera Framework—a graph-based multi-agent system where user intents are transformed into intelligent task plans. These are then delegated to a network of AI agents, contributed by developers across our ecosystem, and equipped with tools compatible with the Model Context Protocol (MCP).

The key components of AgentOpera include:

• Orchestrator and RouterThey translate language inputs into structured, actionable plans and route them to the most suitable agents within the network.
• Agent-Aware Model Serving Platform Our serving layer is optimized for the interactive, back-and-forth nature of agents, differing fundamentally from traditional AI workloads.
• Distributed Agent Runtimes AgentOpera supports agent-to-agent communication, enabling collaboration between agents built by different developers and deployed across heterogeneous environments.
• Hybrid AI Agents By combining on-device and cloud-based agents, we provide personalized experiences, enhanced privacy, and reduced cloud dependence.
• Ecosystem-Ready InfrastructureWith MCP, Framework Adapters, Zero-code Workflow Plugins, and Workflow API Integrations, AgentOpera seamlessly connects with existing systems, services, and third-party agents.

AgentOpera Platform

AgentOpera is not just another AI app—it's a framework and platform for building the future of AI. Here's why our approach is unique:

• One OS, One Network for All AI AgentsWe are moving towards a generalized AI operating system and agentic network using the AgentOpera framework. This means our customers no longer need to subscribe to or manage multiple vertical agent solutions. We believe that a model is the new AI SaaS—open-source foundation models are becoming capable enough to replace traditional SaaS interfaces with more flexible, intelligent UX.
• Tailored Model Serving with Post-Training and RAG Our model layer is optimized with post-training and retrieval-augmented generation (RAG) to serve intelligent agents that understand nuanced tasks and domains, improving both relevance and performance.
• Hybrid Model Serving Infrastructure Our infrastructure supports cost-efficient deployments via hybrid routing across edge devices, smartphones, and the cloud. This not only brings down costs but also ensures scalability and responsiveness.
• Private and Secure by DesignWe enable local and private deployments, further enhanced by Federated Learning, On-device Inference, and Federated RAG. These capabilities provide our customers with greater privacy, security, and data control.

Here are some quick screenshots for such systems.

Figure: The zero-code agent workflow platform, building complex multi-agent workflows with drag-and-drop simplicity.

Figure: Workflow API integration enables AgentOpera to seamlessly connect with existing agents, tools, and data services across the broader ecosystem.

Our existing customers and internal engineering teams are already using the AgentOpera Platform to build a variety of innovative AI applications. For example, one of our customers recently launched their app using the AgentOpera infrastructure—and it has already attracted millions of end users: link.

The Synergy Between AgentOpera and the TensorOpera Model Platform

Our friends are very familiar with our TensorOpera Model Platform (https://TensorOpera.ai) and Federated Learning Platform (https://FedML.ai). The power of TensorOpera now lies in the seamless integration between the AgentOpera framework and the TensorOpera Model Platform, and FedML Platform. While AgentOpera orchestrates multi-agent workflows and intelligent task routing, the underlying model platform provides tailored model serving optimized for agent use cases—enhanced with post-training, retrieval-augmented generation (RAG), and hybrid deployment across edge and cloud. Together, they enable a tightly coupled, high-performance agentic system where models and agents work in harmony to deliver faster, smarter, and more cost-efficient AI experiences.

Looking Ahead

With the AgentOpera AI App, the AgentOpera Framework, and our full-stack AI agent platform, we're building more than just another AI product—we're laying the foundation for a new way to interact with intelligent systems. Whether you're a developer building agents, a company deploying vertical solutions, or an end user looking for smarter tools, TensorOpera offers the flexibility, scalability, and intelligence to meet your needs.

We believe the future of AI software is agentic, distributed, interoperable, and privacy-first. TensorOpera is here to lead that transformation—with tools built for developers, experiences tailored for users, and infrastructure optimized for scale.