Case study

fullstack2025-2026

AquaLog

Progressive Web App for aquarium maintenance tracking. Multi-tank management, water parameter logging with trend analysis, predictive AI alerts, maintenance scheduler, livestock manager, and species compatibility checker. Premium tier with cloud sync.

End-to-end solutions from database to deployment

Field notes

Role

Creator

Read order

Evidence first, then constraint → build → proof. Use the chapter rail to jump sections; orbit to adjacent work from the bottom of the case study.

Full-Stack Nebula✦I-Class Giant

●LIVE

View on GitHub

View Live Site Source Code

Evidence

System surface

No public screenshot on file—generative preview stands in for the visual layer.

Signature viewmyaqualog.com

Open Live Site

myaqualog.com

Story arc

How this shipped

End-to-end solutions from database to deploymentThree beats: what pressed against the work, how the stack answered, and what changed once it was live.

I · Constraint

The brief

Fishkeepers struggle to maintain consistent water quality and track maintenance across multiple tanks. Existing apps are basic spreadsheet replacements.

II · Build

The craft

Built PWA with trend visualization for water parameters, AI-powered alerts predicting issues before they happen, species compatibility database, and gamification to encourage consistent maintenance.

III · Proof

What moved after launch

Live at myaqualog.com. PWA works offline for tank-side logging. Predictive alerts catch water quality issues 24-48 hours early. Gamification layer keeps logging cadence consistent.

Inventory

Stack & signals

Next.jsReactTypeScriptPWARechartsSupabaseAI

Tell me what you're building

If you need someone who can own UI, systems, and AI integration without losing the plot—I'm listening. Contract, advisory, or full-time: we'll find the right shape.

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