OverviewPlatformDigital twinAutonomyDeploymentDiscuss your site

Autonomy and safety

Autonomy should earn trust before it earns authority.

BASALT introduces autonomy in stages, with hard constraints, deterministic fallback, operator approval and auditable evidence built into every level.

L0

Observed

BASALT watches the site, builds the twin and measures prediction accuracy. It cannot propose or act.

L1

Advisory

BASALT proposes plans and explains the trade-offs. Operators remain fully manual.

L2

Approved

BASALT prepares the plan and machine-level work, but a named operator must approve execution.

L3

Supervised

Typical mature operating level

BASALT executes inside a pre-agreed envelope while operators can hold, amend or reverse the plan at any time.

L4

Bounded

Reserved for time-critical actions where waiting would create more risk, such as safety stops, containment or ride-through. Scope is explicitly pre-approved.

What keeps autonomy controllable

Deterministic fallback

Every cell retains deterministic control that can keep the process in a safe operating state without AI. Losing BASALT removes optimisation, not the basic control path.

Hard constraint kernel

Hard limits — safety distance, force, temperature, power import and permits — are enforced outside the models. No agent can negotiate around them.

Rehearsal before reality

Plans must pass simulation and safety checks before they reach hardware.

Evidence by default

Inputs, rejected options, binding constraints, approvals and outcomes are recorded for operator review and audit.

Standards as a baseline

The architecture uses IEC 62443 zones and conduits, ISO 10218 and ISO/TS 15066 for collaborative operation, and the NIST AI Risk Management Framework as design baselines.

BASALT

See what BASALT could change at your site.

Start in observation mode. BASALT builds and validates a live twin against real operations before any autonomous action is enabled. Authority expands only where the evidence supports it.