Gauge / Estimating
A draft with its sources.
Tender scope, job history and rates brought together for estimator review.
AI in practice
Useful work. Visible evidence.
Two demonstrations of AI preparing work for a person to review. Fictional data; real workflow patterns.
Let’s talkAI-narrated demonstration · Sample scenario and authored data.
Read the narration transcript
This is Marshal, a safety and incident response agent from Airon Systems, working behind video analytics on the site's existing cameras.
A PPE alert fires. In these conditions, Marshal reads it as early heat stress and asks for a human call.
The watch escalates. A first aider is already pre-positioned.
Person down. One human decision. And Marshal runs the response workflow. Dispatch, notifications, and incident record building in real time.
Standing rules carry the routine steps. People keep the judgment calls.
Afterwards, the incident record, corrective actions, and a full audit trail. Drafted from the event log, not from memory.
Marshal / Safety response
Context for the next decision.
Field signals, procedures and response actions in one reviewable record.
The design principles
Evidence in view.
People in control.
- Agent roles & orchestration
- Design agents around specific tasks. An orchestrator coordinates their tools, evidence and handoffs.
- Review & exceptions
- Flag gaps and uncertainty. Route material decisions to the accountable person.
- Deployment & traceability
- Run within agreed data boundaries. Keep sources, approvals and actions together for later review.
Let’s make work better
What’s holding your business back?
Let’s find where automation and AI can make a difference.