DataFactZ › Edge AI

Edge AI that watches your sites — and explains itself.

Detection on the device. Reasoning in the cloud. Notifications in the tools you already use. DataFactZ Edge AI is a multi-modal, hardware-agnostic safety and security platform for the enterprise — from industrial sites to schools, venues, and places of worship.

Reasoning in the cloud — the three events that matter

Every camera, microphone, and sensor floods your team with events. Claude reads every one and writes the short briefing your team actually acts on, so they don’t have to. Two hundred raw detections collapse to the three that need a human; the daily briefing is delivered to the channel your team already lives in.

One engine. Every signal.

Vision was just the start. The same detection engine reasons over what it sees, what it hears, and what it senses — so a threat doesn’t have to be visible to be caught.

• Vision — cameras (live in our lab). Frame-by-frame inference on the live feed, proven end-to-end. Detects PPE compliance, people and vehicles, restricted-zone entry, and weapons in frame.
• Audio — microphones (shipping soon). Sound the camera can’t see. Acoustic models flag gunshots and loud impacts, screams and raised voices, glass break, and alarms.
• Environment — sensors (in development). Wire in the sensors you already run. The engine fuses smoke and gas, forced doors and access, motion and occupancy, temperature and climate alongside vision and audio.

Detection library — what it catches

Start with PPE and compliance — proven in production — then switch on detections as your risk demands. Same engine, same dashboard.

• PPE & compliance (live). Hardhats, vests, and restricted zones — our flagship, live in production today.
• Weapons detection (shipping soon). Firearms and edged weapons in frame, flagged the moment they appear.
• Acoustic threats (shipping soon). Gunshots, screams, glass break, and alarms — danger you can hear before you see.
• Intrusion & access (in development). Forced doors, tailgating, and after-hours motion across your perimeter.
• Environmental (in development). Smoke, gas, temperature, and occupancy fused from the sensors you run.
• Custom models (by request). Tell us the scenario that matters to you. We train and deploy the model.

Rules are authored in plain English: describe the scenario in a sentence and Claude builds the structured logic behind it — condition, severity, scope, and notification routing — across every modality.

Critical-alert response — when seconds matter

On a high-severity alert — a weapon, a gunshot, a forced entry — the system escalates on its own. You stay in the loop; you’re never the bottleneck.

1. 00:00 — Threat detected. Example: WEAPON in East Yard, confidence 0.93.
2. 00:01 — On-site alarm + strobe. Deters and warns on the spot.
3. 00:02 — Security notified. SMS + push to the on-site team.
4. 00:03 — Response channel alerted. Microsoft Teams + Email, with the clip.
5. 00:04 — Emergency call placed. Auto-dials 911 or your monitoring center.

Routes to: Phone (911 or your monitoring center), Microsoft Teams, Email, SMS + Push, On-site alarm, Webhook. Human-in-the-loop by default — a supervisor can confirm or stand down any escalation, and every action is timestamped and logged.

Notifications — lands where your team already works

No new console to babysit. The same alert arrives, fully formatted, in Microsoft Teams and email, one tap from the full event in DataFactZ — severity, sustained duration, model provenance, and a button to view the alert in the platform.

Hardware-agnostic — bring your own silicon

Our models aren’t married to one chip. The same detection graph compiles and runs at the edge on the hardware you already trust.

• NVIDIA Jetson — Orin, Xavier, Nano. Our reference edge platform.
• Qualcomm — QCS, Snapdragon. Low-power vision at the edge.
• Intel / x86 — Core, Xeon, OpenVINO. Existing servers and gateways.
• Arm gateways — industrial, rugged, fanless, field-deployable.

One model. Many targets. No re-training.

Two engagement tracks — one platform

Starting from bare walls, or already covered in cameras and edge boxes? Either way you land on the same DataFactZ Edge AI app — and if the hardware is already there, you skip straight to the intelligence.

Full-stack engagement — starting from scratch

Empty site? We assess, plan, procure, install, and configure — then hand you a running platform. Site and risk assessment, visual coverage plan (PDF/HTML), device procurement and setup on any vendor, model rollout and app configuration. Mostly consulting hours up front, then a standard monthly subscription.

Platform subscription — already have devices

Already have cameras and edge hardware on the wall? Keep all of it. Our app plugs into what you have — no rip-and-replace — and goes live in minutes. Connect cameras, microphones, and sensors over ONVIF, RTSP, MQTT, and Azure IoT Edge. Configure rules in plain English. Route notifications per role. Persona dashboards live in minutes. Per-node monthly subscription for enterprise; plans for small and mid-market coming soon.

How it works — from empty site to live monitoring

The full-stack arc — roughly six weeks, fully managed.

1. Assess. We walk your site, talk to your safety and security team, and map the scenarios that matter — compliance, intrusion, and threats.
2. Plan. You get a visual coverage plan: camera, microphone, and sensor placement, plus rule recommendations. We iterate until you approve.
3. Build. We procure and install the edge hardware — Jetson, Qualcomm, or x86 — run cable, and validate the device-to-cloud round trip.
4. Run. Your team logs in. Rules are live. Notifications route, and critical alerts escalate on their own.

Where it ships

Built for the enterprise. Ready wherever security matters — industrial sites, K–12 and higher-ed campuses, houses of worship, venues and events, warehousing and logistics, corporate facilities.

Get started

Book a live walkthrough on your data. We’ll show you the platform running end-to-end and the lab it was built in. Contact: datafactz.ai/edge-ai/contact.

Frequently asked questions

What is the DataFactZ Edge AI platform?

A multi-modal, hardware-agnostic safety and security platform. Detection runs on the device (vision today; audio, sensors, and weapons detection on the near roadmap). Reasoning runs in the cloud with Claude-authored briefings. Critical alerts escalate automatically across alarm, SMS, Teams/Email, and an emergency call to 911 or your monitoring center.

What hardware does DataFactZ Edge AI run on?

NVIDIA Jetson (Orin, Xavier, Nano), Qualcomm (QCS, Snapdragon), Intel/x86 (Core, Xeon, OpenVINO), and Arm industrial gateways. Bring the silicon you already trust.

Is DataFactZ Edge AI production-ready today?

Vision-based PPE and compliance detection is live in production. Acoustic threats and weapons detection are shipping soon. Environmental sensors and automated emergency dispatch are in development — we label each capability honestly.

Can I use my existing cameras?

Yes. The SaaS engagement track plugs into ONVIF, RTSP, MQTT, and Azure IoT Edge devices you already run.

How does emergency dispatch work?

On a high-severity alert, the system fires an on-site alarm and strobe, notifies on-site security by SMS and push, alerts the response channel in Teams and Email, and places an emergency call. A supervisor can confirm or stand down any escalation; every action is timestamped and logged.