Automate visual analysis for healthcare securely on-premise

Process medical imaging, monitor patient safety, and track lab samples without your data ever leaving the building. EyePop.ai On-Premise delivers HIPAA-compliant computer vision with zero latency and no manual tagging.

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Trusted by industry leaders

Get clear, structured data your medical systems can use

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Patient safety monitoring

Automatically detect falls, unauthorized movement, or patient distress in real-time using existing room feeds ensuring rapid response without compromising privacy.

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Medical sample tracking

Track vials, test tubes, and samples through lab workflows. Eliminate manual scanning and ensure 100% traceability for critical biological assets.

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Surgical intelligence

Monitor sterile fields, track surgical instrument usage, and log procedure timestamps automatically to optimize OR efficiency and compliance.

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PPE & hygiene compliance

Verify mask usage, glove protocols, and hand-washing compliance in sensitive zones to reduce infection risks and automate safety auditing.

Smarter care from the start

Seamless Implementation with Zero ML expertise required

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HIPAA-Compliant by design

Your data never touches the cloud. All inference runs locally on your own servers, ensuring total patient privacy and compliance with strict data residency regulations.

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Real-time latency

Analyze video feeds and imaging instantly. No round-trip to the cloud means split-second detection for critical alerts like patient falls or surgical anomalies.

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Feed results directly into EHR & PACS

Seamlessly integrate structured visual data into your Electronic Health Records or PACS workflows. Automate reporting and reduce administrative burnout.

{ How it works }

Your guided path to a deployed solution

Eliminate the guesswork. Every step is streamlined for you. From early scoping through training, refinement, and secure on-premise deployment producing real results.

  • 1
    We talk through your goals and learn what success looks like for you.
  • 2
    You share a few example images or videos. We test whether the task is a good fit for vision AI and outline the simplest path to a working solution.
  • 3
    You collect a small set of images. We help organize them so the system can learn what to look for, then we train an AI model that understands your specific use case.
  • 4
    We choose the right device to run your model. You pick from validated options that match your environment, whether you need edge devices, on premise servers, or lightweight units.
  • 5
    The model is fine tuned and optimized for your hardware. This step makes sure it performs fast and accurately in real conditions.
  • 6
    Your solution goes live. It runs locally and securely, processing your images or video in real time.
Six-step flowchart showing On-Prem process: 1. Discovery call with speech bubble icon; 2. Feasibility with presentation board icon; 3. Model training with computer and gear icon; 4. Optimization with target and arrow icon; 5. Hardware selection with laptop and checkmark icon; 6. Deployment with building and padlock icon.Six-step flowchart showing On-Prem process: 1. Discovery call with speech bubble icon; 2. Feasibility with presentation board icon; 3. Model training with computer and gear icon; 4. Optimization with target and arrow icon; 5. Hardware selection with laptop and checkmark icon; 6. Deployment with building and padlock icon.
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Works with existing IP cameras and medical imaging

No need to rip and replace hardware. EyePop.ai connects to your current RTSP streams, directory folders, or imaging uploads.

Add structured outputs to clinical dashboards

Push tags, alerts, and counts directly into your existing operational dashboards or alert systems via webhooks and standard APIs.

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Powered by EyePop.ai

On-Premise runs on the same proven core as EyePop.ai Cloud.

You get the same workflows, hybrid options, and access to our partner network for labeling, support, and optimization.

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Simple pricing. Scales with you.

Pay only for the boxes you run—no per-camera or per-frame billing.

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Monthly costs

Clear, scalable monthly investment tied only to your active on-prem boxes.

Volume
Price per box
1–10 boxes
$250/mo
10–100 boxes
$200/mo
100–1,000 boxes
$150/mo
1,000+ boxes
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Fixed costs

Client-purchased hardware

You’ll purchase your own hardware, and we’ll guide you through every step. Estimated cost is about $1,500 per box.

Upfront configuration and model tuning

A one-time fee beginning at $5,000 covers end-to-end setup.


See if your organization is a fit

Deploy the world’s most accessible computer vision platform right where your data lives.

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