Predictive AI Analytics
Implementing forward-looking AI models for demand forecasting and lead scoring in tourism and real estate.
The Problem
Businesses in tourism and real estate often rely on historical data and intuition for pricing and lead management. This reactive approach leads to missed revenue opportunities and wasted effort on low-quality leads.
The Solution
We developed and deployed custom predictive AI models to forecast future demand and score incoming leads. For our tourism client, a demand forecasting model adjusts room pricing dynamically based on predicted occupancy. For our real estate client, a lead scoring algorithm prioritizes high-intent buyers, enabling the sales team to focus their efforts where it matters most.
Key Decisions & Architecture
This section highlights the critical engineering and design choices that shaped the final product.
Custom TensorFlow Models
Built custom models in TensorFlow to accurately capture the unique patterns and seasonality of each client's business, delivering more precise predictions than off-the-shelf solutions.
Genkit for AI Flow Management
Used Genkit to manage and serve the AI models via a secure API, ensuring reliable and scalable integration with the clients' existing systems.
Continuous Model Retraining
Implemented an automated pipeline to continuously retrain the models with new data, ensuring they adapt to changing market conditions and maintain their predictive accuracy over time.
Tech Stack
Project Timeline
Outcome & Impact
“The predictive models have given us an unfair advantage. We're now making proactive, data-driven decisions that our competitors can't match.”
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