Layer 01
The Senses
Voice, vision, and live telemetry fused into one picture of the mission — so the aircraft understands what it hears and sees, not just where it is.
SAFETY-FIRST AI FOR AUTONOMOUS DRONES
Autonomy has layers.
Guru is the AI software layer for autonomous drones — a multimodal brain that understands your mission, wrapped around a deterministic safety kernel that never guesses. The model advises. It never touches the motors.
- motor commands ever issued by the model
- 0
- motor commands ever issued by the model
- of decisions recorded and replayable
- 100%
- of decisions recorded and replayable
- deterministic authority between AI and airframe
- 1
- deterministic authority between AI and airframe
THE LAYERS
Three layers. One chain of command.
Most autonomy stacks let a neural network fly the aircraft and hope for the best. Guru separates intelligence from authority: the AI understands and proposes, and a deterministic kernel decides what actually happens.
Layer 02
The Brain
A multimodal AI that reasons about the mission and proposes the next action as a strict, versioned contract. Advisory by design — it can suggest, never seize.
Layer 03
The Kernel
A deterministic supervisor, written in Rust, with sole authority to act. Every proposal is checked against geofence, battery, and vehicle state — and the emergency stop latches until a human clears it.
Fails safe
Lose the model, lose the link — the kernel notices on its own and puts the aircraft in a safe state.
Black-box evidence
Every request, decision, and action is recorded and correlated, so any flight can be replayed and explained.
Any airframe
Replaceable vehicle adapters keep the intelligence portable across drone bodies and flight controllers.
Human override
Arming and takeoff always require explicit confirmation, and a hard stop outranks everything.
HOW IT WORKS
The model proposes.
The kernel decides.
Every action the AI wants to take travels through one narrow, auditable path — and the deterministic kernel is the only thing that can touch the vehicle.
- 1
Understand
Spoken instructions, imagery, and telemetry become structured mission intent — not free-form text steering an aircraft.
- 2
Propose
The brain answers with a strict, versioned action proposal. Anything malformed or unexpected is rejected outright.
- 3
Decide & fly
The kernel validates against geofence, battery, and vehicle state, then executes — or refuses. Critical actions wait for a human yes.
brain → kernel · action proposal
{
"schema_version": "v1",
"request_id": "9f2c41d8",
"action": "take_off",
"params": { "altitude_m": 30 },
"rationale": "Begin tower sweep at inspection altitude.",
"confidence": 0.92
}✓geofence— inside mission boundary
✓battery— 87% — mission margin ok
✓vehicle state— armed and ready
⏸ holding for operator confirmation — takeoff never runs on model say-so
USE CASES
Inspection, first.
Guru is built for work where a missed defect costs more than the flight — and a bad decision costs more than the drone.
Energy
Wind turbines and solar farms swept on a schedule, with every observation tied to evidence you can replay.
Towers & telecom
Close-in structural sweeps at inspection altitude — without putting a climber on the steel.
Pipelines & utilities
Long linear corridors patrolled autonomously, anomalies flagged with location, imagery, and severity.
Bridges & infrastructure
Repeatable flights of the same structure over months, built for comparison — what changed, and how fast.
Industrial facilities
Flare stacks, roofs, and tank farms inspected without scaffolding, shutdowns, or guesswork.
Environmental monitoring
Wildfire watch, coastal erosion, and habitat surveys flown by aircraft that explain what they saw.
Put a brain on board.
Tell us about your aircraft and your mission — we'll show you what Guru can do with them.