Next-Generation Machine Learning for Recommendations and Search
From foundational algorithms to cutting-edge AI, Recombee's research-driven approach combines advanced machine learning techniques to deliver high accuracy and performance at scale for both recommender systems and personalized search.
Research-Driven Innovation
Our commitment to research and development has led to breakthrough technologies like beeFormer - a transformer architecture optimized specifically for recommendation tasks. We’ve also introduced state-of-the-art solutions in scalable collaborative filtering. Our Research and Machine Learning teams collaborate closely to bring the latest innovations into our product.
State-of-the-Art AI
Next-generation AI technologies
- beeFormer architecture.
- LLM-powered recommendations and personalized search.
- Multimodal deep learning.
- Advanced sequence modeling with efficient RNNs.
Advanced ML Core
Sophisticated machine learning methods
- Matrix factorization at scale.
- Deep autoencoder architectures.
- Reinforcement learning.
- Hybrid collaborative filtering.
Retrieval-Based & Heuristic Methods
Optimized implementations of proven techniques
- Exact and approximate sparse and dense vector search.
- Advanced popularity and trends time series modeling.
- Intelligent rotation, explorations, and reminder models.
- Advanced popularity modeling.
- Real-time item discovery.
- Intelligent reminder systems.
Technical Excellence
Deep Learning Innovation
Our advanced deep learning models capture complex user-item interactions using sophisticated neural architectures, allowing for a nuanced understanding of user preferences and content relationships.
Transformer Technology
beeFormer, our custom transformer model, helps solve the cold start problem and improves content relevance and understanding.
Large Language Models
Integration of LLMs enables natural language understanding and generation, powering conversational recommendations and complex content insights.
Real-Time Hybrid Approaches
Our systems dynamically combine multiple recommendation strategies to ensure optimal performance across different scenarios and data conditions.
Unique Features
We’ve engineered our ML models to deliver real-time recommendations and search results across content, products, categories, artists, tags, and more - enhancing discovery in diverse domains.
Why AI from Recombee
Our commitment to research excellence and practical innovation sets us apart. By combining cutting-edge AI with proven methodologies, we build recommendation systems that consistently outperform traditional approaches.
Research Leadership
Pioneering new approaches in recommendation systems.
Scalable Solutions
Enterprise-ready implementations that scale with your needs.
Proven Results
Delivering measurable improvements in user engagement.
Responsibility
Safe AI systems trained to help users.
