AI safety monitoring

Viact

Construction monitoring products combining live streams, alerts, and mobile experiences.

Timeline

2018.06 - 2019.05

Role

Team leadership, full-stack engineering, and mobile plus web product delivery.

Outcome

Helped teams monitor sites more efficiently with realtime alerts and AI-assisted workflows.

ReactReact NativeNestJSTypeScriptTensorFlow

Overview

Construction monitoring products combining live streams, alerts, and mobile experiences.

Why it mattered

Job sites needed faster detection of on-site risks with tools that worked in both mobile and web contexts.

Key decision

Treat mobile and web as one connected monitoring experience instead of splitting them into isolated products.

Hard part

AI-assisted safety workflows had to feel operationally reliable, not just technically impressive.

Outcome

Helped teams monitor sites more efficiently with realtime alerts and AI-assisted workflows.

My contribution

Role: Team leadership, full-stack engineering, and mobile plus web product delivery.

  • Led a small team while shipping across web, mobile, backend, and database layers.
  • Built monitoring products that combined live streams, detections, and alerts.
  • Delivered mobile app functionality tied to AI-assisted recognition workflows.

Outcome

  • Improved site monitoring with connected web and mobile tooling.
  • Helped turn AI detection into a more operationally useful product.

Tech stack

ReactReact NativeNestJSTypeScriptTensorFlow

Product preview

A quick look at the shipped interface and workflow.

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Viact

This case study focuses on the product workflow, technical decisions, and delivery scope rather than a visual screenshot.

Product snapshot

Construction monitoring products combining live streams, alerts, and mobile experiences.

AISafetyWeb + MobileFull-stackRealtime

Implementation notes

AI-assisted safety workflows had to feel operationally reliable, not just technically impressive.

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