Penton Systems / Services / Artificial intelligence
Services · Artificial intelligencePractical AI, wired into real operations.
Agent workflows, monitoring and private AI that fit the systems you already run, with human approval points and an audit trail designed in from the first day.
Six kinds of work.
Each is an engineering service, scoped to one operational problem at a time. Laboratory work is labelled experimental until it has been qualified.
- 01
Agent workflows with approval points
Multi-step agents that gather evidence, reason over it and act across your tools, pausing for a person before any change and logging every call they make.
Service - 02
AI-assisted operations and monitoring
Summaries of logs and alerts, anomalies flagged against thresholds you set, and draft runbook steps for the people on shift. Built on the same monitoring approach as our own Aurora dashboard.
Service - 03
Private and local AI
Self-hosted models on hardware you own, so sensitive data stays on site and tools keep working when the link does not. We test small-model serving and distributed jobs on our seven-node Raspberry Pi cluster.
Lab: experimental - 04
Application integration
Retrieval and language-model features embedded in line-of-business applications through narrow, well-bounded APIs, with inputs and outputs you can inspect.
Service - 05
Intelligent infrastructure management
Monitoring, inventory and ticket data connected so routine events are triaged automatically and the exceptions reach a person with the evidence attached.
Service - 06
Consulting and pilot design
Use-case selection, risk review and a measurable pilot before you commit to a platform, a model or a vendor.
Service
Three rules we do not bend.
Evidence first
Every recommendation cites the logs, metrics or documents it came from, with their source and age. If the evidence is missing, the agent says so instead of guessing.
Humans approve changes
Agents propose; people approve. Nothing destructive runs unattended, a rejection is recorded rather than retried, and nothing proceeds on a timeout.
Private by default
Where the data is sensitive, models and tools run on hardware you own. Where a cloud model is the right call, we say what leaves your network and why.
Small, measured, reversible.
We start with one workflow you repeat every week, prove it in the laboratory, and only then connect it to production.
Define
Write down the decision the system supports, the data it may read, the actions it may propose and who approves them.
Pilot
Bounded tools, read-only first. One workflow, measured against how it is done today.
Qualify
Tested in our laboratory against written criteria, including failure modes, bad inputs and a rollback plan.
Operate
Monitoring, audit logs and documentation ship with the system, so your team can run it without us.
The Intelligence Engine.
A working agent runtime you can run in your browser. It plans with explicit rules rather than a language model, so that every step is inspectable, and every tool call is real.
| Planner | Mission rules evaluated against your inputs; the task graph is shown before anything runs |
|---|---|
| Tools | NOAA space weather, latency to our Orlando node, public orbital elements, RAID reliability models |
| Distributed work | SGP4 propagation and Monte Carlo simulation split across Web Workers on your device |
| Monitoring | Live re-measurement against thresholds you set, with alerts |
| Approval | The run stops until you approve or reject; both branches are recorded |
| Output | A plain-text report with sources, data freshness, findings and your decision |
Capabilities on this page are offered as engineering services. Experimental laboratory work is labelled as such on the Projects page. We do not publish client names, outcomes or figures we cannot show you.