Autonomous agents for IoT & Logistics, under control.
Agentic monitoring and response across sensor and logistics telemetry, on the governed control plane.
Autonomy you can put into production.
The gap between a demo and a deployment in IoT and logistics is governance. Trunnion closes it with policy, approval, and audit built into every run.
Policy-aware by design
Policy-based access control can scope what agents may see and do in IoT and logistics; the implemented policy is verified per release.
A human stays in command
Consequential actions pause at an approval gate. Agents propose the work; your team decides what executes.
Reviewable records by design
Record coverage, supporting traces, integrity, and replay are verified for the exact release.
Deploys where you operate
Run in cloud, on-premise, or fully air-gapped, matched to the compliance posture of the vertical.
Sensor data is continuous, and so is the decision load.
IoT and logistics invert the usual agent problem. There is no shortage of data and no single moment of decision: telemetry arrives continuously, most of it is unremarkable, and the value is in noticing the small fraction that is not, quickly enough to act. That makes autonomy genuinely necessary, because no human watches a sensor feed effectively for eight hours. It also makes governance necessary in a specific way: an agent that escalates everything is useless and one that escalates nothing is dangerous, so the escalation policy itself becomes the controlled artifact, and the record has to show why an exception was or was not raised.
One governed run: a cold-chain excursion.
Every step below is enforced by the control plane rather than left to convention. This is what a governed run looks like end to end in IoT and logistics.
A sensor reports a temperature reading outside its band. The mission composes a validation agent, a context agent, and an escalation agent.
The validation agent checks whether the reading is credible or a sensor fault, using recent history and neighbouring sensors.
The context agent establishes what is affected: which shipment, what contents, which customer commitments, and what the exposure duration was.
The escalation agent evaluates the exception against policy thresholds and proposes a severity and a route.
Notifying a customer or condemning product is consequential and pauses for an operations lead to approve.
The reading, the validation result, the context, the policy evaluation, the decision, and the approver are written to the record.
Where teams start.
The pattern that works is a workflow that is genuinely repetitive, has a clear owner, and fails reversibly. Governance goes in on day one, not after the pilot succeeds.
Cold-chain and condition monitoring
Continuous monitoring with validated exceptions escalated under policy and the reasoning preserved.
Shipment exception triage
Agents establish impact and propose a route; a human decides on customer-facing consequences.
Sensor health and data quality
Agents distinguish genuine excursions from sensor faults so escalation stays credible.
Recurring condition reporting
Reports assembled by agents where the audit trail is the evidence behind each figure.
FizzSense
Agentic monitoring and response across IoT and logistics telemetry. In active development; join the waitlist for early access.
Sensor and IoT intelligence for logistics.
- Runs on the governed Trunnion control plane
- LLM-agnostic model routing
- Cloud, on-premise, or air-gapped deployment
IoT & Logistics, at a glance.
| Product | FizzSense, in development |
|---|---|
| Gated actions | Customer notification, product condemnation |
| Controlled artifact | The escalation policy itself |
| Record | Escalations and suppressions both logged |
| Deployment | Cloud or on-premise |
IoT & Logistics questions.
Do agents run unattended on a sensor feed?
Yes, and that is the point. Validation, context assembly, and policy evaluation run continuously without a person. The gate is on consequences: notifying a customer or condemning product pauses for a human.
How do you stop alert fatigue?
By making the escalation policy an explicit, controlled artifact rather than a threshold buried in code, and by validating readings before escalating so sensor faults do not present as product excursions. Both the escalation and the suppression are recorded, so the policy can be tuned against evidence.
Does this claim FSMA or cold-chain regulatory compliance?
No. Those obligations sit with the shipper and the receiver. Trunnion is designed to support them by enforcing the monitoring and escalation policy consistently and by producing a verifiable record of what was observed and decided.
Which product serves IoT and logistics?
FizzSense is a sensor and IoT intelligence program for logistics. It is in development, with a waitlist open.
Get started
Bring governed AI to IoT & Logistics.
See the control plane run a IoT and logistics workflow, in your environment, from cloud to air-gap.