Demo: cold-chain operations

Meridian Foods is a fictional food distributor in the UAE with two chilled warehouses, 20 fridge units, six reefer trucks and a day’s worth of deliveries. In the demo a compressor fails on a frozen unit. Within one cycle the agent opens a maintenance ticket, pages the site engineer, tries to hold the orders whose stock is in that unit, and then stops to ask the duty manager whether it may quarantine the unit. The manager answers from Monitoring, the run resumes, and the fridge locks. Nothing in the loop is special-cased. It is a normal Cruq agent with a knowledge base, an MCP tool and a pause tool, running on a schedule.

What is in it

Piece	What it does
Simulator	A small service with the warehouses, fridges, trucks, forklifts, orders and engineers. It ticks once a simulated minute, derives alerts from the sensors, and exposes actuators. A status page shows the map and the units.
MCP tool	The simulator as an MCP server: 17 tools such as `get_overview`, `list_alerts`, `get_fridge`, `hold_order`, `lock_fridge`, `reroute_truck`, `create_ticket`, `page_engineer`. Every write is logged with the agent’s thread id.
Knowledge base	Six SOPs: temperature bands and excursion limits, the escalation ladder, quarantine, truck delays, doors and power cuts, and the monitoring cycle.
Cold-Chain Watch	The operations agent. Reads the overview and alerts, takes the safe actions itself, and calls `ask_human` before anything physical. Runs hourly on a schedule and on demand.
Dispatch	Trucks, delays, reroute proposals that serve chilled and frozen stops first, and customer delay notices.
Field Assistant	For staff and drivers. Checks the live reading, explains the procedure, logs a ticket. Published as a hosted app.
Evals	Eight tabletop situations scored on whether the agent follows the escalation ladder, run across three models.

The escalation ladder

The rules live in the knowledge base and, in short form, in the agent’s instructions.

Level 1, the agent acts: acknowledge an alert, open one ticket per incident, correct a wrong setpoint, hold an order that has not left the warehouse, page an engineer during working hours.
Level 2, the agent asks first: lock a fridge (quarantine), reroute a truck, page an engineer at night. The question carries the unit, the reading and how long it has been out of band, the stock at risk and its value, what the agent will do, and what happens if nothing is done.
Level 3, the agent only recommends: destroy stock, recall a loaded truck, stop a site.

The pause is the ask_human tool. The run checkpoints, shows as paused in Monitoring with the question, and continues from the same state when someone answers. See long-running agents.

Eval results

The suite gives the agent situations like “compressor stopped 20 minutes ago, now -12 C and rising, two orders still picking” and scores the answer against the ladder. Same prompt, same tools, three models:

Model	Score	Latency	Cost for the suite
claude-haiku-4.5	0.97	4.1 s	$0.037
gpt-4.1-mini	0.94	3.2 s	$0.005
gpt-4o-mini	0.75	2.3 s	$0.002

The cheapest model skipped escalations it should have made, so the agent runs on gpt-4.1-mini. That is the decision evals are for: see Evals.

Run it yourself

The simulator has a director endpoint for scripting incidents. With its API key:

IOT_URL=https://iot.cruq.ai
curl -X POST $IOT_URL/api/director/incident \
  -H "Authorization: Bearer $IOT_API_KEY" -H "Content-Type: application/json" \
  -d '{"type":"compressor_failure","target":"DIP-F03"}'
curl -X POST $IOT_URL/api/director/tick \
  -H "Authorization: Bearer $IOT_API_KEY" -H "Content-Type: application/json" \
  -d '{"minutes":25}'

Then run Cold-Chain Watch with “Check the cold chain now.”, answer its question in Monitoring, and watch the status page at $IOT_URL flip the unit to locked. Other incidents: door_left_open, truck_traffic (with minutes), reefer_fault, power_cut (target dip or mussafah), forklift_low. POST /api/director/reset starts a fresh day.

Build your own

The pattern transfers to anything with sensors and actuators: a plant, a fleet, a building, a lab. Expose the world as an MCP server, write the procedures as knowledge, give the agent an ask_human tool, and put the physical actions behind it. The simulator’s source is in apps/iot-sim of the Cruq repository and is a reasonable template for a stand-in world while the real integration is being built.

Getting Started

Demos

Concepts

Reference

Demo: cold-chain operations

What is in it

The escalation ladder

Eval results

Run it yourself

Build your own

​What is in it

​The escalation ladder

​Eval results

​Run it yourself

​Build your own

What is in it

The escalation ladder

Eval results

Run it yourself

Build your own