Custom TensorFlow / Keras Model
A neural network we designed and trained ourselves — dense layers with dropout regularization, trained with early stopping and evaluated on a held-out test split — not a wrapper around a third-party API.
← Solutions
◆ Solution We Built
◆ Solution We Built
Staylytics AI: we built it, and deployed it to a real, live website.
Not a prototype, not a slide deck — a production system we designed, built, and deployed end-to-end ourselves — a custom-trained neural network forecasting daily tourist demand for hill-station destinations, live right now at www.demandstay.com.
The Problem
Hospitality demand is volatile, and most operators plan by gut feel.
Hoteliers, tour operators, transport providers, and restaurants in destination towns re-plan staffing, pricing, and inventory every week — usually from instinct and last year's memory, not a forward signal. Staylytics AI fuses weather, search trends, local events, road conditions, and seasonality into a single daily occupancy forecast per destination, so operators can see demand shifts before they hit.
- 5-day occupancy and pricing-pressure forecast per destination, refreshed automatically every week
- Built for travelers, hoteliers, tour operators, transport providers, and restaurants
- Currently live for 7 Himalayan destinations: Manali, Mussoorie, Nainital, Rishikesh, Shimla, Auli, and Leh
- Fully deployed and running in production on AWS — not a prototype
How It's Built
A real ML pipeline, not a spreadsheet with a chatbot bolted on
Multi-Source Feature Pipeline
18 engineered features per destination per day, fusing live weather, Google Trends search interest, local event signals, road conditions, holidays, and rolling occupancy momentum.
FastAPI Backend
A clean, documented forecast API per destination — the same discipline we bring to every backend we build.
Serverless AWS Deployment
Containerized on AWS Lambda, served through CloudFront, refreshed on an automated EventBridge schedule — zero idle servers, the same serverless-first, cost-conscious approach behind every system we ship.
Static, Resilient Frontend
The dashboard never calls the backend directly — it reads pre-generated forecast snapshots, so a data-source outage never takes the site down.
Confidence-Scored Forecasts
Every prediction ships with a confidence score and uncertainty label, so operators know how much to trust a given forecast — not just a bare number.
Live Dashboard
What operators actually see
Road-access scoring fused with a 5-day occupancy and pricing outlook.
Occupancy % and demand score projected forward, not just a single-day snapshot.
Being Straight About It
What the model is trained on today
01
Engineered, Not Scraped
The model currently trains on an engineered feature set modeling realistic seasonal tourism demand patterns — not years of scraped historical booking data.
02
Built to Retrain
The pipeline, architecture, and evaluation harness are already in place to retrain on real occupancy data as it accumulates from live usage.
03
Live and Operating Today
Despite that, the forecast API, deployment, and automated weekly refresh are fully live in production on a real, public website — this is a working system you can visit today, not a slide deck.
Want a forecasting system built for your industry?
Staylytics AI is one example of what we build end-to-end — model, backend, and serverless deployment. Tell us what you'd want to forecast.