# TensorOpera AI

> TensorOpera AI is a full-stack agentic AI platform for building, deploying, and scaling AI agents, models, and GPU workloads across cloud and edge environments.

TensorOpera AI is a full-stack platform built by TensorOpera that spans agent development, model serving, GPU cloud compute, and federated learning. It is backed by the open-source FedML library (Apache 2.0, hosted on GitHub under FedML-AI) and positions itself as an end-to-end solution from model training to production agent deployment. The platform targets developers, ML teams, and enterprises looking to build and scale generative AI applications without managing complex infrastructure.

## What It Is

TensorOpera AI is a cloud-based AI infrastructure platform organized into four interconnected layers: an agentic AI application layer (Teamily AI and AgentOpera Studio), a model and GPU cloud layer (TensorOpera AI Platform), a federated learning layer (FedML), and a mobile/edge AI layer (Fox SLM and Mobile AI SDK). Each layer is designed to work together, enabling co-optimization from agent logic down to GPU scheduling. The platform describes itself as "end-to-end optimized" for agentic AI workloads.

## Platform Architecture

TensorOpera AI is structured around several named components:

- **Teamily AI** — A consumer-facing "Personal AI" app featuring a Super Agent (intelligent routing across specialized agents), an Agent Social Network for multi-agent collaboration, a Discover Agent marketplace, and DeepSearch for context-aware retrieval.
- **AgentOpera Studio** — A developer platform for building agents via prompts, workflows, APIs, or full frameworks. Includes a unified Model API (OpenAI, Anthropic, DeepSeek, Qwen, Llama), MCP server integration, custom Knowledge Bases, and Agent Servers for production hosting.
- **TensorOpera AI Platform** — Covers model serving (TensorOpera Deploy), distributed training (TensorOpera Train), serverless GPU cloud, and an intelligent Model Router for multi-model cost/performance optimization.
- **FedML Platform** — Enterprise-grade federated learning for smartphones (iOS/Android), cross-silo multi-cloud setups, and browser-based JavaScript training.
- **Fox-1 SLM** — A small language model purpose-built for edge-cloud collaborative deployment, available for mobile and IoT environments.

## Open-Source Foundation

The FedML open-source library (github.com/FedML-AI/FedML) underpins the platform. Licensed under Apache 2.0, it provides unified and scalable ML primitives for distributed training, model serving, and federated learning. The repository has accumulated over 4,000 GitHub stars and 767 forks since its creation in 2020. TensorOpera Launch, the cross-cloud scheduler built on FedML, auto-provisions GPU resources and eliminates manual environment setup for training and deployment jobs.

## Compute and Deployment Model

TensorOpera AI offers both serverless and dedicated GPU compute options. Serverless endpoints support popular open-source LLMs and generative AI models with pay-as-you-go billing. Dedicated endpoints allow teams to host custom models with autoscaling, versioning, logging, and monitoring. Supported hardware includes NVIDIA RTX 3090, RTX 4090, A100 80GB, and H100 80GB instances. The platform also supports on-premise cluster management and private or hybrid cloud deployment for enterprise customers.

## Audience and Use Cases

The platform targets three distinct audiences: end users who want a personal AI assistant (Teamily AI), agent developers building and deploying custom agents (AgentOpera Studio), and ML/model developers who need scalable training and serving infrastructure (TensorOpera AI Platform). The federated learning layer additionally serves organizations with strict data privacy requirements, enabling on-device training without pooling raw data. The homepage lists logos of organizations including Qualcomm, Toyota, AWS, Intel, and Aethir as part of its "Trusted by" section, though TensorOpera publishes this claim on its own website.

## Update: AgentOpera and Teamily AI Launch

The TensorOpera blog notes the introduction of AgentOpera AI App and the AgentOpera Framework and Platform, alongside a rebranding of the consumer app to Teamily AI. A blog post also highlights a collaboration with Samsung Electronics around generative AI on mobile devices. The FedML open-source library's latest tagged release is v0.8.9, published in October 2023, though the repository shows continued activity with a last push in October 2025.

## Features
- Full-stack agentic AI platform
- AgentOpera Studio for agent development
- Teamily AI personal AI app with Super Agent routing
- Agent Social Network for multi-agent collaboration
- Unified Model API (OpenAI, Anthropic, DeepSeek, Qwen, Llama)
- MCP server integration
- Custom Knowledge Bases for RAG
- Agent Servers for production hosting
- TensorOpera Deploy for model serving
- TensorOpera Train for distributed model training
- Serverless and dedicated GPU cloud (RTX 3090, RTX 4090, A100, H100)
- Intelligent Model Router for multi-model optimization
- FedML federated learning (smartphone, cross-silo, browser)
- Fox-1 small language model for edge-cloud deployment
- Mobile AI SDK for iOS and Android
- TensorOpera Launch cross-cloud job scheduler
- GPU marketplace for sharing and earning
- Model monetization platform
- On-premise and hybrid cloud deployment support

## Integrations
OpenAI, Anthropic, DeepSeek, Qwen, Llama, AWS, Qualcomm, Intel, Aethir, Samsung Electronics, MCP servers, Docker, Custom Python APIs, Vector databases

## Platforms
WEB, API, ANDROID, IOS, CLI, DEVELOPER_SDK

## Pricing
Freemium — Free tier available with paid upgrades

## Version
v0.8.9

## Links
- Website: https://tensoropera.ai
- Documentation: https://docs.tensoropera.ai/
- Repository: https://github.com/FedML-AI/FedML
- EveryDev.ai: https://www.everydev.ai/tools/tensoropera-ai