Environmental-intelligence networkfor critical infrastructure andautonomous machines

Solana provides shared verification,programmable funding, and settlementwhere distributed participation matters.

Backed by
Superteam Georgia
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Machine-readable view of street geometry and persistent physical features.

QVET observes change in the physical world and turns it into usable state for machines, infrastructure, and operators.

The problem

Digital systems lose value when their view of the physical world goes stale.

Geometry changes. Movement shifts. Hazards appear. QVET creates current, machine-readable state for systems that need to understand and respond to those changes.

An urban intersection at night with vehicles and pedestrians moving through several approaches.

  • Autonomy application

    Moving machines

    Fresh spatial features, change signals, and movement patterns for autonomous vehicles, mapping systems, and field robotics.

    Explore autonomy

  • Operational application

    Managed infrastructure

    Local awareness, decision support, and coordination for transport networks and other distributed physical assets.

  • Exploratory application

    Monitored corridors

    Onboard sensing and wayside units can extend awareness at curves, tunnels, crossings, and other limited-sight-line environments.

Six road scenes comparing optical visibility with range and motion sensing under clear, wet, foggy, and obscured conditions.
All-weather context

Optical detail can fall away while range and movement returns remain available to the machine.

Research visualization of rail geometry, detected objects, and a forward cab view through a curved corridor.
Exploratory corridor direction

Onboard sensing can combine with wayside nodes where curves, tunnels, and crossings limit sight lines.

Condition sequences

Compare what remains usable as optical visibility changes.

Road sequence with partially degraded optical visibility and persistent spatial returns.
Mixed visibility

The QVET system

One intelligence layer across changing environments.

Fixed and mobile nodes observe change. Edge and cloud systems turn it into local decisions or versioned environment data.

Observe
Fixed and mobile nodes capture movement and physical change.
Understand
Quantum Verse resolves local state, persistent features, and coordinated decisions.
Use
Outputs reach controllers, machine APIs, WorldGraph products, and network workflows.

Platform design principles

  • Distributed physical sensing

  • Local response where timing matters

  • Versioned environment state

  • Edge and cloud processing

  • Interoperable machine outputs

  • Privacy-conscious data handling

  • Verifiable network coordination

Quantum Verse

One intelligence system. Different operating loops.

Local control stays at the edge. WorldGraph and network workflows run in the cloud.

01Time-critical edge
Nodes resolve immediate state and select safe local actions without waiting for a cloud or on-chain round trip.
02Environment intelligence cloud
Distributed observations become versioned WorldGraph tiles, freshness signals, and aggregated movement intelligence.

Solana marketplace

Demand funds the places that need new data.

Enterprise customers fund mapping missions in USDC. Accepted contributions are paid from program-controlled escrow with quote-level replay protection.

  1. 01Customer funds a mission
  2. 02Fleet covers requested cells
  3. 03QVET verifies the contribution
  4. 04USDC is released from escrow

Sensor captures, session records, and WorldGraph tiles stay off-chain.

Explore the autonomy application

Traffic application

One example: coordinated traffic state.

Vehicle and queue trackingPCD+TRK

Multi-lane traffic-state estimationPCD+TRK

Product status

Working software. Hardware validation in progress.

Roadside program readiness

The TRL marker below tracks the roadside traffic program. Mobile environment intelligence has a separate capture, replay, and field-validation path.

TRL 5

Current

Relevant environment validation

Breadboard technology undergoes rigorous testing in environments as realistic as possible.

Quantum Verse validated in relevant traffic simulation; multi-radar QVET Node prototype in development.

Built
Deterministic simulation, sensor capture and replay, WorldGraph generation, edge coordination, and Solana marketplace code.
Validating
The roadside traffic program is at TRL 5. Hardware and field interfaces are moving through representative testing.
Next
Representative corridor hardware trials and repeatable mobile sensing validation with measured field data.

From observed state to coordinated action

Traffic coordination is one working application of the platform: local state, neighboring context, and a safe response remain synchronized.

Traffic intelligence

Signals that respond as one corridor.

On the same 16-intersection simulation, coordinated control reduced network waiting time and queue pressure against fixed-time signals.

Simulated corridor under fixed-time signal control, with heavier congestion along the route.
Fixed-time baselineQueues propagate across intersections operating without network-level coordination.
Same simulated corridor under Quantum Verse coordination, with shorter bottlenecks and more balanced flow.
Quantum VerseConnected intersections share traffic state and coordinate timing within safety constraints.

34% lower simulated congestion