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AI-Powered Review Management Platform
Property teams were receiving reviews from multiple booking platforms and needed a reliable way to identify what required attention. This product turns that scattered feedback into prioritized actions.
- Role
- Full-stack SaaS product engineering — migrated an unstable no-code prototype to a production Next.js app with frontend architecture, UX, authentication, backend structure, an AI pipeline, and live Stripe billing.
- Stack
- Next.jsReactTypeScriptFirebaseStripeHostaway APIChart.jsCloudinary
Overview
This started as a no-code prototype that became too fragile to build on — hard to connect to a real database, hard to test, hard to trust. It was rebuilt from the ground up: one dashboard that imports listings automatically, and an AI layer that reads everything so the owner only has to act on the 10-20 things that matter.
Property managers running listings across Airbnb, VRBO, Booking.com, and Google end up with reviews scattered across platforms they'd have to check separately — no shared view, and no realistic way to read hundreds of reviews and know what to actually fix.
Interface
Every platform, one dashboard
Dashboard
Filters, ratings, and platform breakdowns for every connected listing, in one view.
Interface
Every platform, one dashboard
Dashboard
Filters, ratings, and platform breakdowns for every connected listing, in one view.
Key features
From hundreds of reviews to the handful of things worth fixing
Four pieces that turn scattered feedback into a working system — imported automatically, summarized by AI, and tracked from flag to resolution.
Key features
From hundreds of reviews to the handful of things worth fixing
Four pieces that turn scattered feedback into a working system — imported automatically, summarized by AI, and tracked from flag to resolution.
Turns hundreds of reviews into a short list
Instead of reading every review across every platform, the AI pipeline analyzes all of them and surfaces what's actually worth acting on — what's working, what's not, and what to fix first.
One dashboard, every platform
Listings from Airbnb, VRBO, Booking.com, and Google sync into a single view — ratings, response rates, and trends, without switching tabs.
A real review workflow
Flag reviews, leave internal notes, track removal chances, and follow each review's lifecycle from pending to resolved — not just a read-only feed.
Content that writes itself
Scheduled AI-generated blog posts keep the marketing side active without someone writing them by hand every week.
Technical approach
Five decisions that took this from a fragile no-code prototype to a production system — how the data stays trustworthy, how AI costs stay predictable, and how it all holds together.
Built to handle real scale not a demo dataset
01
The external platform stays the source of truth01The external platform stays the source of truth
Review data always comes from the platform it originated on — the app layers its own notes, flags, and AI-derived insights on top, without ever overwriting the original. Refreshing merges new data in instead of replacing what's there.
02
Business logic lives in hooks, not pages02Business logic lives in hooks, not pages
Syncing, AI analysis, pagination, and billing state each live in their own dedicated hook. Pages mostly just compose UI — which kept the codebase workable without needing a heavier state-management library.
03
Two billing models, working together03Two billing models, working together
A subscription covers access and listing limits; a separate token system meters the AI features specifically. That split keeps predictable pricing for the product while protecting against runaway AI costs.
04
An AI pipeline built for scale, not a single API call04An AI pipeline built for scale, not a single API call
Large review sets get split into chunks, processed in parallel, and merged back into one coherent summary — built to handle real volume, not just a demo-sized dataset.
05
Review status computed automatically05Review status computed automatically
Every review gets a computed lifecycle state — pending, grace period, expired, or active — encoding the platform's actual review-timing rules once, reused consistently across every filter and chart.
Results
Shipped, reviewed, and approved by a real partner
Reviewed and approved by Hostaway as an official third-party integration on their partner platform
Live production system — real authentication, real Stripe billing, real review data at volume
AI pipeline built to process hundreds of reviews per run, not a single-call demo
Rebuilt end-to-end from an unstable no-code prototype into a maintainable production app