Astral

The Autonomous Drone Platform.

See it in action

One platform across mobile, quadcopter, and rover — real-time perception and autonomous decision-making in the field

Natural language mission control, try it in our simulator

Environment
Quadcopters
2
Rovers
1

Our simulator is open source and available on GitHub.

Our software will run on your drone, or you can buy our hardware

Autonomous systems with on-device AI. GPS and comm-denied capable, indoor and outdoor.

Quadcopter$9,000
M1-A

M1-A

Autonomous Quadcopter for Any Environment

Jetson Orin Nano 8GB

67 TOPS AI

30 min flight

Aerial platform

GPS & Comm Denied

Full autonomy

IP55

Indoor & outdoor

  • Intel RealSense D435 camera
  • Visual-inertial navigation
  • On-device AI reasoning
  • NDAA compliant compute
Rover$4,000
M1-G

M1-G

Autonomous Ground Rover for Long-Range Patrol

Jetson Orin Nano 8GB

67 TOPS AI

4 hr runtime

Ground platform

GPS & Comm Denied

Full autonomy

IP65

All-weather

  • Intel RealSense D435 camera
  • Visual-inertial navigation
  • On-device AI reasoning
  • NDAA compliant compute

Open Benchmark · 25 VLMs · 10,200 trials

Every end-to-end model lost to a hovering drone.

We tested every major vision-language model in closed-loop flight. The result is why we build a modular stack instead — and why we publish the methodology so you can beat us.

See the full leaderboard
#SystemPos. errorCollisions
1Astral (modular stack)1.04 m0%
2Hover baseline (no motion)9.50 m0%
3Best end-to-end VLM (Gemini 3 Flash)8.70 m

Solutions

Mission-tailored solutions that unlock the full capabilities of autonomous drone fleets. Then customize to your needs.

Defense

NDAA-compliant autonomous systems for ISR, perimeter security, and tactical operations.

Agriculture

Precision farming with crop health monitoring, spraying, and yield optimization.

Infrastructure

Automated inspection of power lines, pipelines, bridges, and critical assets.

Public Safety

Search and rescue, emergency response, crowd monitoring, and law enforcement support.

example.py
from astral import AstralClient

client = AstralClient(api_key=os.environ["ASTRAL_API_KEY"])

# Create a mission
mission = client.missions.create(
    name="Survey Mission",
    waypoints=[
        {"lat": 37.7749, "lng": -122.4194, "alt": 50},
        {"lat": 37.7751, "lng": -122.4180, "alt": 50},
    ],
    config={
        "return_to_home": True,
        "obstacle_avoidance": True,
    },
)

# Deploy to fleet
client.fleet.deploy(
    mission_id=mission.id,
    drone_ids=["drone-001", "drone-002"],
)

Built for Developers

Train pre-configured LLMs or bring your own. Rapidly develop using proven, open source software. Sell your apps on the Astral App Store or build for your specific needs.

Mission Control in Your Pocket

Configure, deploy, monitor and control drone fleets with the Astral app. Build plans and missions confidently. Use our Simulator to run and confirm scenarios before takeoff.

1

Plan Your Mission

Design flight paths, set waypoints, and configure autonomous behaviors.

2

Simulate & Validate

Test your mission in our simulator before deploying to real hardware.

3

Deploy & Monitor

Launch your fleet and monitor real-time telemetry and video feeds.

Astral app — send a command
Astral app — assistant reply
Astral app — drone online

Research-grade autonomy

We benchmarked 25 vision-language models across 10,200 closed-loop flight trials — every one lost to a drone that just hovered. That result is why we build the way we do: we publish on the metric gap in vision-language navigation, modular architectures that separate semantics from geometry, swarm sensing requirements at scale, and Yonder — a public dataset designed to expose when offline perception metrics mislead you in closed loop.

Read our research

Ready to Deploy?

Join enterprises, developers, and innovators building the future of autonomous flight. Get started today.

Open source SDK • Enterprise support available