Three practices, one problem
Most facilities share the same blind spot, just in different places: a condition that has to hold, a step that has to be verified, or a record that has to exist. Each of them can slip quietly. A reading that drifted over a weekend. A product that went out with the wrong label. An exit that stayed blocked through a shift. A corrective action that was done but never signed.
Monitoring, vision, and automation are three ways to close that gap. They share one platform, one alerting path, and one partner responsible for all of it. A temperature sensor and a camera in the same facility end up in the same dashboard, the same workflow, and the same audit record.
How the service works
Most prospects ask the same question on the first call: "You're going to be watching my operation at 2 a.m.?" The honest answer is no, and neither is anyone else. Here is how the service actually works.
The platform runs continuously and autonomously. Sensors report on their own schedule over LoRaWAN to a cellular gateway at your site. Cameras run their models on an edge device, and only events leave the building. All of it lands in one platform. Nobody is watching a screen. The platform is.
Alerts go to the people who can act on them. When a reading drifts out of range or a camera flags a missing label, the alert goes to your manager, your supervisor on shift, or whoever is on call. Not to a monitoring center. Not to a queue. Directly to the person who needs to walk over and look. The alert includes what happened, what to check, and how long it has been going on.
Records are automated, and AI never writes them. Weekly logs, audit-ready reports, and incident records are generated by fixed rules, timestamped, and delivered to your inbox or your auditor's. AI does the seeing and the drafting. The compliance chain stays rule-based, so every record can be traced back to the reading and the rule that produced it.
The principal handles design, installation, and the things software can't. Site walks. Camera placement and the glare that only shows up at 3 p.m. Hardware selection. Network setup. Workflow tuning. Retraining a model when your packaging changes. Root cause when something is genuinely broken. Quarterly check-ins. Real conversations when a real person is needed.
This is how practices like this have worked for years. The platform is the always-on layer. The principal is the relationship and escalation layer. Both pieces are required and neither is faked. Whether the platform sits on our account or yours changes the invoice, not the design.
Who runs Geigyr
Geigyr's principal brings eleven years across Splunk and Databricks in technical sales, sales engineering, and solutions architecture, including work with industrial and manufacturing customers. That work meant building streaming data pipelines for plant equipment, running proofs of concept on a customer's real data, and answering the hard technical questions before a customer committed. Multiple Databricks certifications. And most recently, hands-on computer vision work: training and validating detection models and deploying them on edge hardware.
Direct, technical work with everything Geigyr deploys: LoRaWAN sensors, MQTT, edge computing, vision models, dashboards, and workflow automation.
Most importantly, the person who designs your system, installs the hardware, and answers the phone has designed and deployed systems like this before. That experience is the difference between a system that works on the first day and one that still works a year later.
Who is accountable
When you work with Geigyr, the person who scopes your system is the person responsible for it, from the first site walk through the life of the deployment. Others may work on the installation or the models over time. The accountability doesn't move. The principal signs off on the design, stands behind the result, and is the one you call when something needs to change.
This is by design, and it is how the buyers in our market prefer to buy: owner-operators, plant managers, quality directors, warehouse operators. They want to know who is accountable. They want that person to answer the phone.
What you can count on
We tell you when we're not the right fit. If the problem is better solved by a different vendor or a spreadsheet, you'll hear that on the first call.
Demos are labeled as demos. Every image and dashboard on this site is a real system or a demonstration that says so. No fictional case studies, no borrowed logos.
AI never writes a compliance record. It can see, draft, and flag. Your people decide, and the record is generated by rules you can read.
Nothing locks you in. The hardware is yours outright. Dashboards, alert rules, and workflows export as files you can load into your own instance of the same platforms, and your full history exports on request. If we host it for you, that stays true.
