Cold-chain excursion response
A temperature excursion is assessed instantly, product risk computed, a field crew dispatched, the quality decision recorded.
Cold-chain excursion response
- Cold room CR-4: 8.6 °C, threshold 8 °C; in excursion for 14 minutes
- Last 2 hours pulled; second sensor confirms, compressor current low
- Excursion real, trend +0.3 °C / 10 min; 10 °C expected in 45 min
- Lots in CR-4: 18 lots, 3 product families, most sensitive: vaccine lot L-2291
- Stability rule: 2–8 °C, cumulative excursion tolerance 4 hours @ ≤ 12 °C
- Cumulative 14 min + forecast 45 min < 4 hours → product risk low, monitoring continues
- Service order FS-2026-8812: compressor check, priority urgent, nearest technician 25 min
- Transfer decision if the vaccine lot is affected → quality manager approved “hold and monitor”
- WhatsApp to the site lead: status, technician ETA, monitoring window; record written to the quality file
- ■completed
Simulation · derived from real agent definitions · every agent can be built by dialogue with the Autonomous Agent and validated with a test corpus
Threshold breach from a cold-room or vehicle sensor
Affected lots identified, dispatch done, quality decision and customer notification completed
Agents
Cold-Chain Supervisor
Decomposes the objective, delegates to agents, manages approval points, merges the result.
Sensor Agent
Confirms the excursion and computes its duration
get_sensor_seriesvalidate_readingcompute_excursionQuality Agent
Assesses risk against product stability rules
get_lots_in_locationsearch_stability_rulesscore_product_riskField Agent
Dispatches a technician and informs the customer
create_service_orderdispatch_techniciansend_whatsappSteps
| # | Kind | Agent | What happens | System | ms | tok |
|---|---|---|---|---|---|---|
| 01 | ingest | Cold-Chain Supervisor | Cold room CR-4: 8.6 °C, threshold 8 °C; in excursion for 14 minutes | IoT Platform | 200 | — |
| 02 | tool | Sensor Agent | Last 2 hours pulled; second sensor confirms, compressor current low | IoT Platform | 420 | — |
| 03 | reason | Sensor Agent | Excursion real, trend +0.3 °C / 10 min; 10 °C expected in 45 min | — | 600 | 520 |
| 04 | tool | Quality Agent | Lots in CR-4: 18 lots, 3 product families, most sensitive: vaccine lot L-2291 | WMS / Lot Tracking | 440 | — |
| 05 | retrieve | Quality Agent | Stability rule: 2–8 °C, cumulative excursion tolerance 4 hours @ ≤ 12 °C | Stability Rules (vector) | 480 | 460 |
| 06 | verify | Quality Agent | Cumulative 14 min + forecast 45 min < 4 hours → product risk low, monitoring continues | — | 560 | 400 |
| 07 | write | Field Agent | Service order FS-2026-8812: compressor check, priority urgent, nearest technician 25 min | Field Service | 520 | — |
| 08 | approval | Cold-Chain Supervisor | Transfer decision if the vaccine lot is affected → quality manager approved “hold and monitor” | — | 2,400 | — |
| 09 | notify | Field Agent | WhatsApp to the site lead: status, technician ETA, monitoring window; record written to the quality file | WhatsApp Business API | 260 | — |
Device fleet anomaly triage
Telemetry anomalies from thousands of devices are clustered, root-cause candidates listed, one incident reaches the right team.
Staged OTA update rollout
Firmware rolls out in 1% → 10% → 100% stages; a health gate at every stage, human approval for critical fleets.
Time to move from experimenting with AI to transforming with it.
In a 30-minute discovery session we take your 2–3 priority business problems, show a live demo of a similar scenario, and draft a roadmap that starts with the Value layer.
- Your 2–3 priority problems
- Live demo of a similar scenario
- Roadmap starting with value analysis