// Platform · CapabilitiesPlan · Act · Explain

Plan, decide, act, explain — under policy.

Goal-driven agents that reason over sensor state, take action in connected systems, and document every step in an audit log. Built for environments where being wrong has a cost.

HTN+LLM
Hybrid planning
<1s
Decision latency
100%
Auditable
Policy
Guardrailed

The problem

The capability surface.

HTN + LLM planning

Hierarchical task networks ground LLM reasoning. The planner knows your operating model; the LLM handles the language.

Typed action grammars

Models can only emit calls that match a typed signature. Tool hallucination has no surface area.

Policy guardrails

Typed policies enforce scope, approval thresholds, and rate limits. Agents physically cannot exceed authority.

Decision audit ledger

Every plan, every tool call, every override recorded with timestamp, identity, and reasoning trace.

Multi-agent coordination

Agents share state through the object graph. Conflicts surface as events, not silent races.

Operator-in-the-loop

Configurable approval modes — auto, attended, supervised. Operators see what agents will do before they do it.

Six steps, under one second.

An agent is not a prompt. Each cycle perceives current state from the graph, plans against your operating model, is checked by policy, acts through typed tool calls, and writes an explanation — every pass, without exception.

Authority is checked, not assumed.

Every proposed action passes a typed policy gate evaluated server-side. Scope, thresholds, rate limits, clearance and reversibility are checked before anything executes — so an agent cannot widen its own authority.

Autonomy is earned per action type.

There is no global autonomy switch. Each action type sits at one of four levels, and moves up only after a shadow period proves its precision. Irreversible actions stay advisory permanently.

Every cycle leaves a record.

One real agent run, written immutably: what it saw, what it planned, what policy said, what it did, and what it held for a human. This is the artefact an inquiry or regulator reads.

Agents share state, never messages.

Agents coordinate through the object graph rather than talking to each other. Two agents claiming the same object produce a visible conflict event for an operator to arbitrate — not a silent race.

Agentic AI for environments where being wrong has a cost. Plan, act, explain — every step under policy, every decision auditable.

What this delivers.

See Agentic Orchestration running in your environment.

A 60-minute architecture review with our solutions team. We map your sensors, your systems, and the workflows where this capability moves the needle.