Powered by advanced AI algorithms combining BM25 retrieval, semantic embeddings, and LLM generation for personalized recommendations.
Our AI-powered recommendation system combines multiple advanced technologies to deliver the most accurate and personalized smartphone suggestions.
Combines classical BM25 with modern BGE embeddings and neural reranking for superior accuracy.
Response times under 2 seconds with optimized vector search and caching strategies.
Deployed on GCP with Kubernetes, Docker, and auto-scaling for enterprise reliability.
Comprehensive observability with Prometheus and Grafana dashboards.
Personalized recommendations with persistent session history in PostgreSQL.
Horizontal Pod Autoscaler handles traffic spikes with 3-10 dynamic replicas.
OpenAI & Groq integration with fallback mechanisms for reliable generation.
Price-based categorization (Budget, Mid-range, Premium, Flagship) with dynamic filtering.
Health checks, metrics endpoints, error handling, and comprehensive logging.
Built with modern, scalable technologies to ensure high performance and reliability.
A modular, cloud-native architecture designed for scalability and performance.
RESTful API designed for easy integration and comprehensive functionality.
Try our live demo and discover how AI-powered recommendations can transform your smartphone search experience.
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