TensorFleet
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VSCode Plugin

Code from Your Desktop,
Run Fleets in the Cloud

The complete development environment for drone software. Write code locally, deploy to cloud simulations, train AI models, and push directly to physical hardware.

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Features

Everything You Need in One IDE

Streamline your drone development workflow with powerful tools and integrations.

Code from Your Desktop
Write, debug, and test drone code directly from VS Code with intelligent autocomplete and real-time syntax checking.
Cloud Fleet Management
Run and manage fleets of drones in the cloud. Deploy simulations and test missions at scale without physical hardware.
AI Model Training
Train AI models directly from your IDE. Integrate with popular frameworks like TensorFlow and PyTorch for computer vision and autonomy.
Reinforcement Learning
Build and train reinforcement learning models for autonomous behavior. Simulate thousands of iterations in accelerated time.
Version Control Integration
Seamlessly integrate with Git. Track drone code changes, manage configurations, and collaborate with your team.
Deploy to Hardware
One-click deployment from simulation to physical drones. Manage firmware updates and configuration across your fleet.

From Development to Deployment

The TensorFleet VSCode extension brings professional-grade drone development to your fingertips. No more context switching between tools—everything you need is integrated into your favorite editor.

  • Unified development environment for drone software
  • Real-time collaboration with cloud-based simulations
  • Integrated debugging with drone telemetry visualization
  • Support for ROS2, PX4, and ArduPilot frameworks
  • CI/CD pipeline integration for automated testing
  • Remote fleet monitoring and diagnostics

Workflow

How It Works

From code to cloud to drone in minutes.

1

Install the Extension

Install the TensorFleet extension from the VSCode marketplace. Authenticate with your TensorFleet account and you're ready to go.

2

Write & Test Code

Use familiar Python APIs to control drones. Test in local simulators or spin up cloud-based drone fleets for large-scale testing.

3

Train AI Models

Leverage reinforcement learning and computer vision models. Run thousands of training iterations in accelerated cloud simulations.

4

Deploy to Hardware

One-click deployment to physical drones. Manage firmware, configurations, and over-the-air updates for your entire fleet.

Early Access

Join the TensorFleet waitlist

Tell us your use case—get docs, samples, and adapters as they ship.

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