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From Zebra

What the technology promises, and what it means on site

Selected Zebra posts, each with what it translates to in a Turkish deployment.

The posts on this page belong to Zebra Technologies' official LinkedIn account and press releases; LinkedIn posts are displayed through LinkedIn. The commentary is by Orsa AIDC.

23 September 2026

In Hospitals, AI Moves From the Back Office to the Bedside

Our take

The picture Zebra paints is familiar on the hospital floor: a large share of nursing time goes to documentation and hunting for missing equipment rather than patient care. In Turkey that translates into scanning wristband barcodes at medication administration, tracking mobile assets like infusion pumps and beds with RFID/BLE, and consolidating secure care-team messaging onto a single clinical device. The hard part is not the hardware but integration with the hospital information system and infection control: devices must tolerate disinfectants, wireless coverage must hold across corridors, and every scan must land directly in the patient record. Building that end-to-end setup in healthcare is exactly the work we do.

Read the release at the source

17 September 2026

Zebra KC401: A Kiosk Is Only as Good as Its Integration

Our take

The real value of the KC401 is answering the "do you have it, what does it cost" question without pulling an associate off the floor — which is exactly where Coresight's figure of roughly four associates' capacity per store comes from. In Turkey, the hard part is never the hardware: it's keeping the stock and price data on that screen in real-time sync with your ERP, making sure in-store networking doesn't drop, and siting the IP65 unit so it fits your actual cleaning routine. For sites already running CC6000 units, reusing the same mounts and infrastructure is a genuine advantage — a drop-in swap moves far faster than a greenfield rollout, and planning those migrations and building the integration layer is the core of what we do.

Read the release at the source

2 September 2026

Hospital Callback Times: A Device Problem or a Workflow Problem?

Our take

What actually shortens a nurse's callback time isn't the handheld itself — it's the alert reaching the right person at the right moment, and that's precisely what Zebra is demonstrating here. In Turkey, the crux of such a deployment is integration with the hospital information system and the nurse call platform: if the terminal doesn't know who is on shift or which patient belongs to which team, it's no better than a walkie-talkie. Then there are the clinical realities — disinfectant-ready housings, silent alerts in intensive care, seamless Wi-Fi roaming between floors, and a battery plan that survives a full shift. On the healthcare side, our job isn't handing over devices; it's fitting that workflow onto the systems you already run.

Read the release at the source

10 August 2026

What is missing or mispriced on the shelf — instantly, by camera

Our take

What Zebra shows here shortens the time store staff spend on shelf checks: point the device at the shelf and missing stock, wrong prices and planogram deviations are listed at once. In Türkiye the critical part of such a deployment is not the hardware but the integration with your existing stock and pricing systems — the camera reports what it sees, but what it *should* have been comes from your ERP. Building that integration is central to what we do in retail.

View on LinkedIn

21 July 2026

What modernizing frontline workflows is actually worth

Our take

The interesting part of this study isn't the headline numbers but the breakdown of which workflow drives which result: supply chain and maintenance in manufacturing, point of sale in retail, shipping and loading in T&L. In Turkey we usually start from the same problem — the hardware has been bought, but the workflow still runs the way it did on paper, so neither the speed nor the data gain materializes. To genuinely accelerate a pick-pack or loading step, the terminal screen has to map one-to-one onto the steps in your WMS/ERP so the operator makes a single decision per scan; building that mapping takes longer than mounting the devices, but it's where the difference comes from. The AI expectation depends on the same foundation: if the floor isn't producing clean, timely data, there's nothing for a model to say.

Read the release at the source