Try It Live
Click Analyze Device Health to auto-scan your browser-accessible device info, optionally supplement it with metrics you can pull directly from your OS using the built-in guides, and receive an AI health assessment with a score, risk factors, and replacement recommendation. If replacement is warranted, fill in the procurement form and submit — a structured request is emailed to IT instantly.
How It Works
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Auto-scan — The agent reads what your browser exposes: operating system, CPU core count, available RAM (Chrome/Edge), battery level, screen resolution, and browser storage quota. These are displayed instantly, no input required.
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Asset database callout — In a live internal deployment, this step is skipped entirely: device age, model, disk usage, and utilization history are pulled directly from your asset management system (Jamf, Microsoft Intune, ServiceNow CMDB, or a custom HRIS). The demo surfaces this integration point prominently so stakeholders understand the production architecture.
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Manual supplement — For metrics the browser can't read (device age, disk usage %, average CPU and RAM utilization, reported symptoms), the form provides optional fields. Each field includes an expandable "How to find this" guide with step-by-step instructions tailored to your detected OS (Windows or macOS).
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AI health assessment — GPT-4o-mini scores the device across five dimensions (Age, Performance, Storage, Reliability, Security), each out of 20 points. The overall score drives a recommendation: REPLACE (0–40), MONITOR (41–65), or KEEP (66–100). The AI returns a plain-English reasoning summary, a list of specific risk factors, and a ready-to-send procurement justification.
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Procurement request — If replacement is recommended, the agent pre-fills a procurement form: suggested replacement model (OS-aware), priority level, shipping preference, and an editable AI-drafted justification. Review and submit — the request is emailed to your IT team immediately.
What This Demonstrates
| Capability | Description |
|---|---|
| Browser hardware detection | Reads OS, CPU, RAM, battery, screen, storage via Web APIs |
| AI scoring & reasoning | Multi-dimension health assessment with structured JSON output |
| OS-aware contextual help | Platform-specific guides appear based on detected OS |
| Asset database integration point | Clear callout showing where Jamf/Intune/CMDB would connect |
| Human-in-the-loop | Manager reviews all data before anything is submitted |
| AI-drafted communications | Procurement justification drafted from structured device data |
| Email delivery | Structured HTML procurement request routed to IT |
From Demo to Production
This demo evaluates one device at a time using browser-available data. A production deployment would connect to your asset management platform and evaluate your entire fleet on a schedule.
Real-World Challenges
| Challenge | Why It Matters |
|---|---|
| Asset inventory accuracy | Most CMDB/asset databases are 60–80% accurate — devices go untracked, creating blind spots |
| Heterogeneous fleet | Windows, Mac, Linux, and mobile each have different health indicators and lifecycle expectations |
| Budget cycle alignment | Replacement recommendations need to align with annual IT budget planning, not just technical need |
| Vendor management | Preferred vendors, volume discounts, and lead times affect procurement decisions |
| Employee disruption | Replacing a device mid-project has a productivity cost — timing matters |
| Sustainability / disposal | Lifecycle management includes secure data wiping, recycling compliance, and asset recovery |
Cost Estimates (Monthly)
| Component | Starter | Growth | Enterprise |
|---|---|---|---|
| AI API | $10–40 | $40–150 | $150–600 |
| MDM/CMDB integration (Jamf, Intune, SCCM) | $100–400 | $400–1,500 | $1,500–5,000 |
| Procurement system integration | $50–200 | $200–600 | $600–2,000 |
| Asset tracking infrastructure | $0–100 | $100–400 | $400–1,500 |
| Total monthly | ~$150–600 | $600–2,500 | $2,500–8,000 |
ROI Definition
- Primary metric: Reduction in unplanned device failures — target 40–60% fewer emergency replacements
- Secondary metrics: Extended useful life for devices that don't need replacing, standardized procurement
- Break-even: Typically 3–6 months
- Concrete example: An unplanned laptop failure costs $800–1,200 in emergency procurement premium + 1–3 days of lost productivity ($400–$1,200). For a 200-device fleet experiencing 15 failures/year, proactive replacement saves $18,000–$36,000/year vs ~$8,000/year tool cost.
Technology Stack
- AI Model: OpenAI GPT-4o-mini
- Email Delivery: Google Workspace SMTP (Nodemailer)
- Browser APIs:
navigator.userAgent,navigator.hardwareConcurrency,navigator.deviceMemory,navigator.getBattery(),navigator.storage.estimate(),window.screen - Frontend: React client component with multi-phase flow, auto-detect on mount, collapsible OS-aware guides
- Backend: Next.js API route (serverless) — two actions:
analyze(AI scoring) andprocure(email send)
Want This for Your Business?
A production deployment connects to your asset management platform (Jamf, Microsoft Intune, ServiceNow CMDB, or Lansweeper) to pull device records automatically. Hardware age, model, purchase date, incident history, and utilization data are evaluated on a schedule — flagging at-risk assets before they fail. Procurement requests route to your existing ticketing system (ServiceNow, Jira, Freshservice) with full audit trail. A full deployment typically takes 1–2 weeks and starts at $2,500.