Blog
We Develop Global Recommendation Service and Share Our Insights Here
New Features for a Better Personalization Experience
Like most of the world, the majority of 2021 was spent on home office or in isolation - which left us with all the time to be invested in work (and Netflix :) ) and improving UX for our clients. We are now happy to share new features we can offer to reach new levels of personalization.

Advancing Your Career in Artificial Intelligence with prg.ai and Recombee
At Recombee, we have always collaborated with academia — after all, five of our co-founders graduated from the Czech Technical University in Prague, one of the largest and oldest technical universities in Europe, and most of them hold a Ph.D. degree.

Linear Methods and Autoencoders in Recommender Systems
Linear regression is probably the simplest and surprisingly efficient machine learning method. It should be the method of your first choice, according to the famous KISS principle. Also, it often works better than sophisticated methods, because it is...

Recombee Real-Time AI Recommendations as the New Destination in Segment
Segment has enabled its users to enjoy Recombee personalization services without the need to leave their platform and with minimum coding involved. With a few simple clicks, domains using Segment can upgrade their services to maximize the digital experience for their customers.

Recombee and Kentico Xperience: Guide to One-on-One Personalization
Recombee expanded its integration options - and now is available at the Kentico Xperience platform! Analyzing different types of personalization, we look into why Kentiko chose our AI-powered recommendation engine over manual segmentation.

Recombee in 2020: New Features and Improvements
We know that this year has been quite challenging for many people, including ourselves. However, today we want to focus entirely on the positive (no pun included) side of the year and the stuff we are the proudest of.

Deep Learning for Recommender Systems: Next basket prediction and sequential product recommendation
Accurate “next basket prediction” will be enabling next generation e-commerce — predictive shopping and logistics. In this blogpost, we will discuss the deep learning technology behind next basket...

How interdisciplinary collaboration can accelerate AI innovation
In a world where innovation is the new standard, Recombee uses the power of interdisciplinary collaboration to stay at the cutting edge of innovation. Partnering up with the leading player in the food industry (Bofrost) and academia (FIT CTU), allowed Recombee to hold a student competition to create AI which can shape the future of the food industry.

Introduction to personalized search
Personalized search should take into account user preferences and interactions of similar users. We combined search engine and recommender.

Recombee in 2019: New Features and Improvements
This year was really huge for us. We worked on new features so hard that we almost forgot to write a blog post about them :)
Check out our new client-side integration support and deploy personalized recommendations faster
We knew we had to bring something new to the table, when participating as a Beta Startup at Web Summit, the largest technology conference…

Machine Learning for Recommender systems — Part 2 (Deep Recommendation, Sequence Prediction, AutoML…
In the first part of our talk, we discussed basic algorithms, their evaluation and cold start problem. Below we show how deep learning…

Machine Learning for Recommender systems — Part 1 (algorithms, evaluation and cold start)
Recommender systems are one of the most successful and widespread application of machine learning technologies in business. There were many…

Migrating to Recombee from Microsoft Cognitive Services Recommendations
Microsoft has recently discontinued the Recommendations within the Azure Cognitive Services (MCSR). If you used this service, you are…

Personalized push notifications enabled by artificial intelligence
Recent progress in artificial intelligence enables us to design proactive AI systems. Whereas traditional recommender systems produce…

Personalized recommendations in 10 minutes
We have just released a video tutorial that will guide you through the integration of the Recombee recommendation service to your…

Evaluating Recommender Systems: Choosing the best one for your business
Together with the endless expansion of E-commerce and online media in the last years, there are more and more Software-as-a-Service (SaaS)…
The value of personalized recommendations for your business
The e-commerce boom makes online environment more competitive. Internet retailers seek competitive advantages and a personalized experience…

Recommender systems explained
In this article, I overview broad area of recommender systems, explain how individual algorithms work.

Generating client libraries for Recombee recommendation API
Client libraries help programmers to integrate an API into their systems in a faster, easier and more readable way. We have recently published clients for Ruby and PHP, and we wish to provide clients for other major programming…

Personalized recommendations in Ruby
For those of you, who develop in Ruby, we prepared a simple client application enabling you to benefit from our personalized recommendations.

Artificial Intelligence in the Cloud
At Recombee, we “think big”, and prefer making big leaps in technology over taking small steps. Our team has been involved in data science and artificial intelligence research for many years. Beginning in 2012, we began to capitalize our knowledge and experience, developing products which…
