# Recombee > Recombee is a Recommender as a Service — real-time AI personalization, recommendations and search delivered through a REST API, SDKs and no-code widgets. This site covers the product, the industries it serves, customer case studies and the engineering blog. To integrate Recombee — REST API, SDKs, no-code widgets, catalog feeds and integration guides — use the developer documentation, a separate site indexed at https://docs.recombee.com/llms.txt. ## Product - [AI-Powered Real-Time Recommender](https://www.recombee.com/index.md): Recommender as a Service with an intuitive RESTful API & SDKs tailored by data scientists. - [Real-Time Content-Based Recommendation Engine](https://www.recombee.com/content-recommendations.md): Personalize user experience with a real-time recommendation engine. Suggest the most relevant content for users based on their behavior and preferences. - [Pricing](https://www.recombee.com/pricing.md): Start an unlimited 30-days trial. Choose to upgrade to usage-based plans or continue with a Free Plan. - [Recommendation Engine for Real-time Personalization](https://www.recombee.com/product.md): Use the most advanced recommendation engine powered by machine learning and follow the trend of hyper-personalization. - [Product Recommendation Engine Tailored by Data Scientists](https://www.recombee.com/product-recommendations.md): Personalize the product offer for every individual customer. Utilize real-time personalization for a better user experience using Recombee's recommender system. - [What Makes Our Recommendation Technology Unique](https://www.recombee.com/technology.md): We utilize deep-learning, collaborative- (e.g. matrix factorization), and content-based filtering (e.g. image processing algorithms) in our recommender systems. - [Examples of Personalized Recommendations](https://www.recombee.com/where-to-use.md): Generate product or content recommendations. Personalize home page, product view, watch next, read next, email and others - [Configurable Recommender with Real-Time Analytics](https://www.recombee.com/admin-ui.md): Explore performance metrics and configure recommendations to reflect your needs. Use a simple and user-friendly interface designed for all your team members. - [Features](https://www.recombee.com/features.md): Discover the mechanics behind Recombee's smart recommendations. - [Recommendations & Search | Features](https://www.recombee.com/features/recommendations-search.md): Recombee’s real-time recommendation engine adapts instantly to user interactions and content updates, delivering personalized experiences as they happen. - [Accelerated Integration to Popular Platforms Using Our Plugins](https://www.recombee.com/integrations.md): Recommender as a Service with an intuitive RESTful API & SDKs tailored by data scientists. - [AI-Driven Recommendation Engine Suitable for Every Industry](https://www.recombee.com/specialized-recommendations.md): Recombee finds a solution for every industry. Our recommendation engine personalizes and delivers content based on individual user taste and preferences. - [Business Rules | Features](https://www.recombee.com/features/business-rules.md): Craft custom rules to highlight specific categories, brands, editor-picked content, local deals, and more—delivering diverse recommendation boxes and email campaigns. - [Full Control with Scenario Settings | Features](https://www.recombee.com/features/full-control-with-scenario-settings.md): Customize recommendations with Recombee’s flexible Scenario Settings to perfectly align content with your product strategy. - [Integration | Features](https://www.recombee.com/features/integration.md): Integrate easily with a well-structured REST API and SDKs, complemented by catalog feed processing, No-Code widgets, and ready-made integrations with key platforms like Segment. - [Real-Time Analytics & Insights | Features](https://www.recombee.com/features/real-time-analytics-insights.md): Track engagement with detailed, customizable reports available in our Admin UI, offering insights into how users interact with recommendations and your platform. - [Scalability | Features](https://www.recombee.com/features/scalability.md): Built as a high-performance, real-time distributed system, Recombee scales to support even the most demanding environments. ## How It Works - [How It Works](https://www.recombee.com/how-it-works.md): Recombee recommendation engine was from the very beginning designed as a modern, secure, real-time, and horizontally scalable distributed cloud system. - [AI & Machine Learning | How It Works](https://www.recombee.com/how-it-works/ai-and-machine-learning.md): Uncover the cutting-edge technologies we use to power your personalized recommendations. - [Data & Results | How It Works](https://www.recombee.com/how-it-works/data-and-results.md): Learn about the types of data Recombee processes to tailor your users' experiences. - [Performance at Scale | How It Works](https://www.recombee.com/how-it-works/performance-at-scale.md): Find out how we ensure rapid delivery of recommendations, regardless of traffic volume. ## Industries & Use Cases - [Engage Readers with Personalized, Real-Time Recommendations](https://www.recombee.com/domains/articles-news-media.md): Recombee’s advanced 1:1 content personalization is designed to boost engagement metrics and maximize subscriber lifetime value while preserving the editorial voice. - [Drive Repeat Visits With Personalized Deals](https://www.recombee.com/domains/deal-aggregators.md): Surface the right promotions before they expire based on user behavior and live inventory to increase click-through rates, partner yield, and repeat visits. - [Drive Revenue Growth With Personalized Product Discovery](https://www.recombee.com/domains/e-commerce.md): Guide shoppers to products they’re most likely to buy with real-time 1:1 recommendations that increase conversions, average order value, and repeat purchases. - [Get Better-Fit Applications With Smarter Job Matching](https://www.recombee.com/domains/jobs-boards-hr-networking.md): Recommend relevant roles based on each candidate’s context and real-time behavior to increase job discovery, applications, and qualified matches. - [Keep Listeners Coming Back With Personalized Recommendations](https://www.recombee.com/domains/music-podcasts.md): Recommend the next song, artist, album, or playlist based on listener context and real-time behavior to drive discovery, engagement, and repeat listening. - [Drive Marketplace Growth With Real-Time Recommendations](https://www.recombee.com/domains/p2p-marketplaces.md): Connect buyers with listings they’re most likely to engage with to increase discovery, conversions, and repeat activity. - [Boost Property Discovery With Personalized Recommendations](https://www.recombee.com/domains/real-estate.md): Surface relevant listings instantly based on real-time user signals and evolving preferences to reduce search fatigue and drive higher-quality inquiries. - [Win Every Fan With Real-Time Sports & Live Event Recommendations](https://www.recombee.com/domains/sports-and-live-events.md): Keep fans watching longer and coming back for more. Recombee’s personalization engine delivers instant, hyper-relevant sports and live event content to every viewer across games, highlights, replays, and news. - [Increase Bookings With Relevant Travel Recommendations](https://www.recombee.com/domains/travel-trips.md): Turn lookers into bookers with recommendations that adapt to traveler preferences, context, and real-time behavior to drive bookings and repeat stays. - [Maximize Engagement With Real-Time Video Recommendations](https://www.recombee.com/domains/video.md): Surface the right content at the right moment with recommendations that adapt in milliseconds. Increase watch time, completion, subscriptions, and retention across every device. ## Case Studies - [Unlocking 15% More Actor Runs for the World’s Largest Marketplace of Tools for AI](https://www.recombee.com/case-studies/apify.md): As the marketplace expanded, Apify needed search and recommendation capabilities that could scale with its rapidly growing catalog while delivering personalized discovery from the very first interaction. - [Personalized Streaming Experience Tailored 1:1 in Real-Time](https://www.recombee.com/case-studies/audiomack.md): Thanks to Recombee, Audiomack provides its 5 million daily active users with a personalized streaming experience tailored one-on-one in real-time. - [Increasing Click-Outs by 21% for Pepper | Case Study](https://www.recombee.com/case-studies/pepper.md): The integration of Recombee's AI-driven product recommendations successfully established a personalized user experience in real-time across multiple platforms (iOS, Android, and web) in different countries. - [Driving Growth for the World’s Leading Pet Marketplaces | Case Study](https://www.recombee.com/case-studies/pet-media-group.md): Pet Media Group aims to streamline pet adoption in Europe, leveraging Recombee technology to help pet's discovery and engage users. - [Content Recommendations Drive Showmax Engagement Rate](https://www.recombee.com/case-studies/showmax.md): Showmax has chosen Recombee as a long term strategic partner for personalization service to develop a solution that understands preferences of individual users. - [Slickdeals Boosts CTR With Personalized Recommendations](https://www.recombee.com/case-studies/slickdeals.md): Slickdeals is the largest social platform for shopping with a high number of products and dynamic content. Recombee helped to pick the best deals for customers. - [Increasing Engagement by 35% for The Telegraph, The UK’s Leading News Publisher](https://www.recombee.com/case-studies/the-telegraph.md): To further strengthen content discovery and reader engagement, The Telegraph partnered with Recombee to support real-time, personalized recommendations, designed to work alongside strong editorial standards rather than replace them. - [Real-Time User Generated Content Personalization](https://www.recombee.com/case-studies/9gag.md): Recombee's user-generated content recommendations helped 9GAG fully personalize their homepage infinite scroll and increase multiple KPIs. - [Replacing Outdated Recommendation Algorithm With Easy to Integrate Solution Across 5 Media Brands](https://www.recombee.com/case-studies/unfiltered-media-group.md): The next-generation media company, Unfiltered Media Group, LLC, seeks ways in growth markets to create connections with enthusiastic audiences using both print and digital magazines, books, videos, online courses, apps, festivals, and more, with which they have rich experience. - [Personalization Examples and Case Studies](https://www.recombee.com/case-studies.md): Learn how Recombee helped top brands to increase KPIs through ad personalization, email personalization, jobs recommendation, and many others - [Driving +35% Increase in Playbacks Across Video Platforms](https://www.recombee.com/case-studies/diagnal.md): Recombee's recommendation engine integration with DIAGNAL's OTT solution led to a +35% increase in user playbacks and +9% growth in paying subscribers across multiple video platforms. - [Kunzmann Increases Shopping Cart Volume With Personalization](https://www.recombee.com/case-studies/autohaus-kunzmann.md): Recombee provides product recommendations for e-commerce site Autohaus Kunzmann that significantly increase its shopping cart volume and click-through rate. - [Product Recommendations to Achieve Optimal Click-Through Rate](https://www.recombee.com/case-studies/cooklist.md): Recombee's advanced search personalization was implemented into the core of the product and helped increase the click-through rate by 27%. - [Personalized Listing to Skyrocket Buy Actions & CTOR](https://www.recombee.com/case-studies/crexi.md): Recombee improved Crexi's platform on multiple touchpoints through personalized property suggestions, emailing campaigns, and sophisticated search results. - [Design Group Lifts Purchases by 52% With Personalization](https://www.recombee.com/case-studies/design-group.md): To meet the strategic goal of full personalization, Design Group chose Recombee to deliver a tailored recommendation solution. - [Economia Drives Pageviews With Personalized News](https://www.recombee.com/case-studies/economia.md): Economia, a media company, decided to explore power of AI for personalization. Based on superb A/B test performance, Recombee was chosen as winner of tender. - [Content Recommendations Lead to Increase in CTR and Views](https://www.recombee.com/case-studies/ftv-prima.md): Recombee’s high-tech recommender engine brought a significant increase in the volume of advertising consumed online. - [FTV Prima Boosts Engagement with Content Recommendations](https://www.recombee.com/case-studies/ftv-prima-content.md): Recombee's AI-powered recommendations increased CTR, views, and ad impressions for FTV Prima’s online magazines, driving higher engagement and recirculation. - [itison Boosts Newsletter ROI Through Email Personalization](https://www.recombee.com/case-studies/itison.md): Recombee has provided itison with AI-powered solution that utilizes machine learning recommendations for weekly emailing to personalize individual’s experience. - [Real-Time Collaborative Filtering & Text Processing](https://www.recombee.com/case-studies/mafra.md): Recombee’s smart content recommendations helped Mafra personalize news to their readers across three different sites and personalize emailing to their premium users. - [Driving up to 477% Higher Onboarding Engagement for a Global Digital Library](https://www.recombee.com/case-studies/perlego.md): To boost early activation and long-term retention, Perlego partnered with Recombee to deliver reliable, personalized recommendations across key user journeys. - [Driving 32% Higher Job Application Conversion for Serbia’s Leading Employment Platform](https://www.recombee.com/case-studies/poslovi-infostud.md): In the first week of A/B testing against the existing recommender, Recombee exceeded the predefined +20% success threshold across all measured metrics, leading to the decision to fully migrate. - [Real-Time AI-Based Personalization Increased ROI](https://www.recombee.com/case-studies/reliving.md): Recombee's AI product recommendations allowed Reliving to personalize the shopping experience for their customers while increasing desired KPIs and ROI. - [Generating 160 Million Product Recommendations per Month](https://www.recombee.com/case-studies/segundamano.md): Segundamano is a leading online marketplace in Mexico. Recombee provided Segundamano with a recommendation engine built on collaborative filtering-based models. - [Increase Average Order Value | Targito](https://www.recombee.com/case-studies/triola.md): Recombee was applied to help shoppers find the right product in the right style and size as quickly as possible. ## Blog - [News and Media Personalization | Recombee AI](https://www.recombee.com/blog/breaking-the-news-the-role-of-ai-in-modern-journalism.md): Artificial Intelligence (AI) has rapidly transformed the media industry in recent years. Automated news production, trend analysis and personalised content... - [Linear Methods and Autoencoders in Recommender Systems | Blog](https://www.recombee.com/blog/linear-methods-and-autoencoders-in-recommender-systems.md): Linear regression is probably the simplest, surprisingly efficient machine learning method and it should be the method of your first choice. - [Making Linear Autoencoders Work for Large Scale Recommendation Systems | Blog](https://www.recombee.com/blog/making-linear-autoencoders-work-for-large-scale-recommendation-systems.md): We introduce ELSA, a scalable linear model that is basically a shallow autoencoder. What is interesting is that ELSA is not only more scalable... - [Item Discovery and Search | Recombee AI](https://www.recombee.com/blog/modern-recommender-systems-part-1-introduction.md): Over the last ten years, we have been working on an universal and domain agnostic recommender system. Now, we can finally say that we have succeeded. - [Modern Recommender Systems - Part 2: Data](https://www.recombee.com/blog/modern-recommender-systems-part-2-data.md): Data used by modern recommenders and how we can measure progress towards goals - [Modern Recommender Systems - Part 3: Objectives](https://www.recombee.com/blog/modern-recommender-systems-part-3-objectives.md): Learning objectives of recommender systems and personalized search. - [AI Personalization Through Content Recommendations | Video](https://www.recombee.com/blog/real-time-personalization-of-content-with-ai-powered-recommendations.md): Do you manage a publishing company, online gaming platform, or a streaming site and are thinking about how to improve the user experience? Read on. - [AI Adoption in the Media Industry | Recombee Personalization](https://www.recombee.com/blog/the-ai-revolution-in-the-media-industry.md): In today's digital age, personalization has become the cornerstone of the media industry. Whether it's tailoring content recommendations, enhancing UX, or... - [Matrix Completion | Recombee AI Recommender](https://www.recombee.com/blog/inductive-matrix-completion-how-to-improve-recommendations-for-cold-start-users-and-items-by-incorporating-their-attributes.md): Matrix completion has found use in a wide range of domains. Its potentially most successful application is as a collaborative filtering technique for RSs. - [Recombee Item Segmentations | Recombee Recommender](https://www.recombee.com/blog/recombee-item-segmentations.md): Item Segmentations are Recombee's original and elegant solution to various advanced tasks related to hierarchical and relational data. The feature provides a flexible way to group items (products or pieces of content) into segments. - [Recommendation Engine | Blog](https://www.recombee.com/blog/recommendation-engine.md): Recommender as a Service with an intuitive RESTful API & SDKs tailored by data scientists. - [Blog](https://www.recombee.com/blog.md): Recommender as a Service with an intuitive RESTful API & SDKs tailored by data scientists. - [2025 Sneak Peek](https://www.recombee.com/blog/2025-sneak-peek.md): This year is already off to an exciting start, and we’re rolling out new tools to improve efficiency and optimize recommendations. Here’s what’s available and what’s coming next. - [A 2025 Research Retrospective](https://www.recombee.com/blog/a-2025-research-retrospective.md): In 2025, I became Head of Research at Recombee. I knew it would be a challenge: and I wasn’t wrong. Recombee is a leader in recommendation-as-a-service, with thousands of clients across a wide range of domains. - [AI Assistants Know Your Preferences, Even Better Than You Do](https://www.recombee.com/blog/ai-assistants-know-your-preferences-even-better-than-you-do.md): Recommender systems and ethical controversies - [AI News and Outlook for 2026](https://www.recombee.com/blog/ai-news-and-outlook-for-2026.md): Here’s what caught my attention in AI research lately, and where things might be heading in 2026. After 25+ years in this field, the pace has gotten hard to keep up with. I’m trying to make sense of what actually matters from the flood of papers and demos. - [Are You Here to Stay? Unraveling the Dynamics of Stable and Curious Audiences in Web Systems](https://www.recombee.com/blog/are-you-here-to-stay-unraveling-the-dynamics-of-stable-and-curious-audiences-in-web-systems.md): Why do influencers frequently request their subscribers to enable all notifications for their channels? This practice stems from their awareness that not all subscribers are regular... - [Non-stationary Multi-Armed Bandits | Recombee Recommender](https://www.recombee.com/blog/bandit-models-exploiting-popularity-and-curiosity-to-recommend-trending-content.md): Let us start with an example of one of the most fundamental recommender system problems: cold-start recommendation (CSR). - [Build vs. Buy: Deciding the Best Approach for Your Recommender System](https://www.recombee.com/blog/build-vs-buy-deciding-the-best-approach-for-your-recommender-system.md): When it comes to deciding between buying a recommender system and building one from scratch, the choice isn’t always straightforward. Both options come with their own set of pros and cons... - [How Regionalization-Based Recommendations Can Improve Your Operations](https://www.recombee.com/blog/how-regionalization-based-recommendations-can-improve-your-operations.md): From ancient trade routes to modern urban planning, geography has consistently shaped human decisions and opportunities. Today, in the world of online business and personalized recommendations, geography remains equally influential, even though the effects aren’t always immediately obvious. - [Complete Personalization Experience | Recombee AI](https://www.recombee.com/blog/innovative-personalization-features-for-2023.md): The digital sphere is moving; users' expectations for personalization are rising and with that so are our Recombee features improving. - [Introducing beeFormer: A Framework for Training Foundational Models for Recommender Systems](https://www.recombee.com/blog/introducing-beeformer-a-framework-for-training-foundational-models-for-recommender-systems.md): In the fast-evolving world of recommender systems, understanding both how users interact with content and the actual content itself is crucial. Many existing recommender systems struggle to balance these two aspects... - [Digital Media Personalization | Content Recommendations | Blog](https://www.recombee.com/blog/keeping-up-with-digital-media-convergence.md): At Recombee, we felt the transition within the media industry accelerated by the pandemic. OTT and CTV consumption ballooned at a significant rate. - [Key Trends in News & Media for 2025 and the Role of AI-Powered Solutions](https://www.recombee.com/blog/key-trends-in-news-and-media-for-2025-and-the-role-of-ai-powered-solutions.md): The way news is produced, delivered, and consumed keeps shifting, and as we move through 2025, a few big changes have become impossible to ignore. - [Looking Back at 2025](https://www.recombee.com/blog/looking-back-at-2025.md): 2025 marked 10 years of Recombee. A decade of building personalization from first principles, shaped by research, real-world deployments, and close collaboration with partners across industries. Here’s what defined the year. - [Making Recommendations Fairer: A New Way to Guarantee Exposure for All](https://www.recombee.com/blog/making-recommendations-fairer-a-new-way-to-guarantee-exposure-for-all.md): As recommender systems become more widespread across digital platforms, concerns around fairness are coming to the forefront. Standard relevance-based ranking techniques, while effective... - [Mid-Year Roundup: 2026 So Far](https://www.recombee.com/blog/mid-year-roundup-2026-so-far.md): The digital world continues to change at an incredible pace. As technology evolves and user expectations keep rising, creating experiences that feel relevant has never been more important. - [New Feature: A/B Testing](https://www.recombee.com/blog/new-feature-ab-testing.md): Personalization is never finished. Every change to your recommendation strategy raises new questions. Should you boost fresh content? Change used Logic? Introduce new filters? - [New Features Real-Time Recommendation Engine | Blog](https://www.recombee.com/blog/new-features-for-a-better-personalization-experience.md): Recombee continued improving UX for our clients and are now happy to share latest features to reach new levels of personalization. - [No-Code Search Widget: Personalized, Powerful, Effortless](https://www.recombee.com/blog/no-code-search-widget-personalized-powerful-effortless.md): At Recombee, we don't just excel at recommendations – we provide powerful full-text search capabilities too. Our Quick, No-Code Search Widget exemplifies this, offering a seamless, customizable search experience that's quick to integrate and enhances the utility of our recommendation engine. - [Product Highlights from 2025](https://www.recombee.com/blog/product-highlights-from-2025.md): In 2025, we focused on making advanced personalization easier to implement, scale, and maintain across products and platforms. Here’s a look at the key product updates we released last year. - [Increase Your Customer’s Success With Recombee Engine | Blog](https://www.recombee.com/blog/recombee-in-e-mail-marketing-a-partner-success-story-with-ryzeo.md): Adding a recommender service to your emailing campaigns gives each client tailored product recommendations in all of their emails - [Recombee Partners With Axinom to Enhance Video Streaming Experiences](https://www.recombee.com/blog/recombee-partners-with-axinom-to-enhance-video-streaming-experiences.md): This collaboration is set to introduce a new era of personalized and engaging digital user experiences. - [Recombee Partners with The Telegraph to Deliver AI-Driven Personalisation to Millions of Readers](https://www.recombee.com/blog/recombee-partners-with-the-telegraph-to-deliver-ai-driven-personalisation-to-millions-of-readers.md): Prague, 11th September 2025 – Recombee, a leading AI-powered recommendation platform, has announced a strategic partnership with The Telegraph, one of the United Kingdom’s most respected media brands. - [Recombee Real-Time AI Recommendations in Segment | Blog](https://www.recombee.com/blog/recombee-real-time-ai-recommendations-as-the-new-destination-in-segment.md): With Recombee, Segment users can enjoy online personalization services and upgrade their sites to maximize the digital experience for their customers. - [Recombee Research 2024](https://www.recombee.com/blog/recombee-research-2024.md): Recombee has always been deeply connected to academia, with four of our six co-founders holding Ph.D. degrees. Over the years, our investment in research has grown alongside our company and the increasing demand for advanced features in the market. - [Analysing Training Data Using RepSys | Blog](https://www.recombee.com/blog/repsys-opensource-library-for-interactive-evaluation-of-recommendation-systems.md): When building modern real-world artificial intelligence systems, it is increasingly important to validate that the system works correctly. - [SHIELD: The Universal Framework Making AI Search Safer for Everyone](https://www.recombee.com/blog/shield-the-universal-framework-making-ai-search-safer-for-everyone.md): Imagine searching for "glass tubing" and getting recommendations for drug manufacturing equipment. As AI-powered search becomes ubiquitous — from online marketplaces to social networks — the stakes for getting it wrong have never been higher. - [The Building Blocks of Privacy-Friendly Personalization](https://www.recombee.com/blog/the-building-blocks-of-privacy-friendly-personalization.md): Personalization can be achieved without compromising user privacy. While many personalization systems have historically relied on practices now considered intrusive, like third-party cookies, cross-site tracking, or opaque data sharing, Recombee has taken a different approach from the start. - [2024 Wrap-Up](https://www.recombee.com/blog/2024-wrap-up.md): As we wrap up 2024, let’s take a moment to celebrate the milestones we’ve achieved together. Your collaboration and feedback have been at the heart of our progress. Here’s a quick recap of last year’s highlights. - [Partnerships That Open New Opportunities | Blog](https://www.recombee.com/blog/advancing-your-career-in-artificial-intelligence-with-prg-ai-and-recombee.md): Recombee maintains a close relationship with prg.ai and CTU that offer individual career growth in areas of machine learning and other tech tracks. - [AI News and Outlook for 2024 | Blog](https://www.recombee.com/blog/ai-news-and-outlook-for-2024.md): We look at the most interesting research directions and assess the state of knowledge in key areas of AI. - [Company News | Blog](https://www.recombee.com/blog/company-news.md): Recommender as a Service with an intuitive RESTful API & SDKs tailored by data scientists. - [Elevate Your Personalization Strategy with Recombee's Innovative Features](https://www.recombee.com/blog/elevate-your-personalization-strategy-with-recombees-innovative-features.md): The digital landscape and customer preferences and behavior are changing faster than ever now. To help our clients stay on top of the game, our team has focused on developing innovative features... - [How Interdisciplinary Collaboration Can Accelerate AI Innovation | Blog](https://www.recombee.com/blog/how-interdisciplinary-collaboration-can-accelerate-ai-innovation.md): In a world where innovation is required, Recombee utilizes interdisciplinary collaboration to speed up innovation and shape the future of the food industry. - [Recombee Insights: The Next Level of Analytics in Recombee UI](https://www.recombee.com/blog/insights-the-next-level-of-analytics-in-recombee-ui.md): The advanced analytics tool that delivers real-time, in-depth customer insights, customizable KPI tracking, and easy data visualization to streamline your product strategy. - [Integrations | Blog](https://www.recombee.com/blog/integrations.md): Recommender as a Service with an intuitive RESTful API & SDKs tailored by data scientists. - [Is this comment useful? Enhancing Personalized Recommendations by Considering User Rating Uncertainty](https://www.recombee.com/blog/is-this-comment-useful-enhancing-personalized-recommendations-by-considering-user-rating-uncertainty.md): Picture this: you're on the hunt for the perfect new smartphone, browsing through your favourite online electronics store. The online store’s recommendation engine pops up with what it thinks could be your possible next gadget love... - [New Features | Blog](https://www.recombee.com/blog/new-features.md): Recommender as a Service with an intuitive RESTful API & SDKs tailored by data scientists. - [Partnerships | Blog](https://www.recombee.com/blog/partnerships.md): Recommender as a Service with an intuitive RESTful API & SDKs tailored by data scientists. - [Personalization | Blog](https://www.recombee.com/blog/personalization.md): Recommender as a Service with an intuitive RESTful API & SDKs tailored by data scientists. - [Recombee in 2020: New Features and Improvements | Blog](https://www.recombee.com/blog/recombee-in-2020.md): 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. - [Recombeelab's 2023 Research Publications | Blog](https://www.recombee.com/blog/recombeelabs-2023-research-publications.md): Recombeelab, a joint research laboratory of Recombee and the Faculty of Information Technology at the Czech Technical University in Prague, experienced a highly productive year in 2023, publishing a series of insightful and impactful papers in the field of recommendation systems. ## FAQ - [FAQ](https://www.recombee.com/faq.md): Explore the Most Asked Questions - [Features | FAQ](https://www.recombee.com/faq/features.md): Explore the Most Asked Questions - [How It Works | FAQ](https://www.recombee.com/faq/how-it-works.md): Explore the Most Asked Questions - [Personalized Search | FAQ](https://www.recombee.com/faq/personalized-search.md): Explore the Most Asked Questions - [Recommendations | FAQ](https://www.recombee.com/faq/recommendations.md): Explore the Most Asked Questions - [Are targeted advertisements the same thing as AI-powered recommender systems? | FAQ](https://www.recombee.com/faq/are-targeted-advertisements-the-same-thing-as-ai-powered-recommender-systems.md): No. Targeted advertisements and AI-powered recommender systems are distinct technologies that are frequently conflated. **Many common ad formats - such as aband - [Can recommendation systems be used to convert free users into paying subscribers? | FAQ](https://www.recombee.com/faq/can-recommendation-systems-be-used-to-convert-free-users-into-paying.md): Yes. Recommendation systems can be explicitly optimized for subscription conversion, not just engagement. For free-tier users on subscription-based platforms, * - [We cache recommendations to reduce server load. Could that actually be hurting our engagement numbers over time? | FAQ](https://www.recombee.com/faq/does-caching-recommendations-hurt-engagement.md): Yes, caching recommendations can degrade engagement over time if the system is not notified of repeated exposures. When a recommender receives no feedback on it - [How can item categories be used to control which recommendations a user sees? | FAQ](https://www.recombee.com/faq/how-can-item-categories-be-used-to-control-which-recommendations-a-user-sees.md): Item categories give teams direct levers for shaping recommendation output. **Categories can be used to filter items out of results entirely, boost the probabil - [How did recommender systems originate, and what distinguished early systems from modern personalized ones? | FAQ](https://www.recombee.com/faq/how-did-recommender-systems-originate.md): Early recommender systems grew out of information retrieval (IR) systems in the early 1970s, and their defining limitation was that they produced the same outpu - [How do content streaming platforms balance supporting niche creators with optimizing for mainstream user engagement? | FAQ](https://www.recombee.com/faq/how-do-content-streaming-platforms-balance-niche-creators-and-engagement.md): Content streaming platforms treat the balance between mainstream and niche content exposure as an explicit recommendation objective, promoting diverse content t - [What role do neural text embeddings play in recommending items that have few or no user interactions? | FAQ](https://www.recombee.com/faq/how-do-neural-text-embeddings-help-with-cold-start-recommendations.md): Neural text embeddings allow recommender systems to surface relevant cold-start items - those with few or no interaction history - by computing similarity based - [How do recommendation objectives get defined for a specific platform and its individual use cases? | FAQ](https://www.recombee.com/faq/how-do-recommendation-objectives-get-defined-for-a-specific-platform.md): Recommendation objectives for a specific platform are typically defined through careful analysis of user needs, business requirements, and strategic goals, emer - [My users don't behave the same way across a session - sometimes they're in research mode, sometimes just browsing. Can a recommender actually handle that, or does it just pick one mode and stick with it? | FAQ](https://www.recombee.com/faq/how-do-you-handle-different-user-behaviors-in-a-session.md): A single recommendation scenario will not cover both modes well. Running multiple recommendation scenarios in parallel - one optimized for discovery, one for pu - [We have freemium users I want to convert to paid subscribers. Can I actually tune the recommender to push them toward subscription - or is that too manual to set up? | FAQ](https://www.recombee.com/faq/how-do-you-handle-freemium-user-conversion.md): Yes. Recommendation systems can be configured to serve business objectives beyond engagement, including subscription conversion. For freemium users, the system - [A lot of our users aren't logged in. Do recommendations for them just default to "most popular" and stop there? | FAQ](https://www.recombee.com/faq/how-do-you-handle-recommendations-for-anonymous-users.md): No, anonymous users receive session-based recommendations, not just popularity lists. Multi-armed bandit algorithms can personalize within a session using signa - [When I hear "targeted ads", I assume the recommender is behind it. Is that actually how it works? | FAQ](https://www.recombee.com/faq/how-do-you-handle-targeted-ads.md): No, targeted advertising and recommender systems are distinct systems with different data inputs. Recommender systems work only with anonymized interaction data - [In what recommendation scenarios does a user's geographic location become a critical input? | FAQ](https://www.recombee.com/faq/how-does-geographic-location-affect-recommendation-quality.md): Geographic location is critical in scenarios where users are interested in items physically tied to a place, such as real estate listings, job postings, or loca - [How does incorporating user background attributes such as skills or interests affect recommendation quality in domains with sparse interaction data? | FAQ](https://www.recombee.com/faq/how-does-incorporating-user-background-attributes-affect-recommendation-quality.md): In domains where users interact infrequently - such as job platforms or professional networks - interaction history alone is insufficient to build a reliable pr - [What strategic risk does neglecting cold-start item coverage create for a product catalog-driven business? | FAQ](https://www.recombee.com/faq/how-does-neglecting-cold-start-coverage-affect-business-outcomes.md): Neglecting cold-start coverage means newly added items receive no recommendation exposure until they accumulate interactions, creating a self-reinforcing cycle - [We're launching new products every week. How quickly can they actually get recommended to the right users if they have no clicks yet? | FAQ](https://www.recombee.com/faq/how-quickly-can-new-products-get-recommended.md): New items don't have to wait for their first clicks before entering recommendations. Modern recommender systems generate neural embeddings from item text and im - [How should a business weigh GDPR and data privacy requirements against the need for rich user data to drive personalization? | FAQ](https://www.recombee.com/faq/how-should-a-business-weigh-gdpr-and-data-privacy-requirements.md): Regulatory frameworks like GDPR can be treated as a structural advantage rather than a constraint. **Data minimization strategies and pseudonymization allow rec - [Is the growth in recommender system adoption a trend we need to take seriously, or is it already plateaued? | FAQ](https://www.recombee.com/faq/is-the-growth-in-recommender-system-adoption-a-trend-we-need-to-take-seriously.md): Recommender system usage has been growing consistently and shows no signs of slowing. The number of recommendations served to an average active online user has - [What types of data sources does a modern recommender system rely on to generate personalized recommendations? | FAQ](https://www.recombee.com/faq/what-data-sources-does-a-modern-recommender-system-rely-on.md): Modern recommender systems draw on three primary data categories: an item catalog, a user catalog, and a history of user-item interactions. **The item catalog s - [Beyond clicks, what interaction data should we actually be sending in to get meaningfully better recommendations? | FAQ](https://www.recombee.com/faq/what-interaction-data-should-we-send.md): Click data alone is a weak signal - partial consumption data is significantly more informative. Tracking what fraction of content a user actually consumed - the - [What is driving the continued growth in the volume of recommendations served to online users? | FAQ](https://www.recombee.com/faq/what-is-driving-the-continued-growth-in-the-volume-of-recommendations.md): The growth in recommendation volume is driven by three compounding factors: **more internet users globally, more time each person spends online, and a rising nu - [What is the strategic significance of recommendation systems becoming pervasive across virtually every major online platform? | FAQ](https://www.recombee.com/faq/what-is-the-strategic-significance-of-recommendation-systems-becoming-pervasive.md): Recommender systems have become the most influential machine learning technology in consumer-facing products, with the average active online user receiving hund - [What is the strategic value of investing in image-based neural embeddings for a marketplace where sellers upload their own product photos? | FAQ](https://www.recombee.com/faq/what-is-the-strategic-value-of-investing-in-image-based-neural-embeddings.md): In user-generated marketplaces, sellers are unlikely to provide structured text descriptions, making image embeddings the primary available signal for item simi - [What makes recommendation objective design particularly complex for platforms like job boards or dating sites? | FAQ](https://www.recombee.com/faq/what-makes-recommendation-design-complex-for-job-boards-dating-sites.md): Job boards and dating sites face recommendation objectives that are more complex than single-sided platforms because they must optimize for the satisfaction of - [What was the significance of the GroupLens system in the history of personalized recommendations? | FAQ](https://www.recombee.com/faq/what-was-the-significance-of-the-group-lens-system.md): GroupLens, introduced in 1992, was one of the first systems to base recommendations exclusively on user historical interactions - specifically, explicit ratings - [Why are historical items that are no longer available to users still stored in the item catalog? | FAQ](https://www.recombee.com/faq/why-are-historical-items-still-stored-in-the-item-catalog.md): Historical items are retained in the catalog because **they are essential for measuring similarity between users who interacted with those items in the past**. - [Why is content discovery a standalone recommendation objective rather than a byproduct of relevance optimization? | FAQ](https://www.recombee.com/faq/why-is-content-discovery-a-standalone-recommendation-objective.md): Content discovery is treated as an independent objective because relevance optimization alone tends to surface familiar or already-popular content, which does n ## Comparisons - [Why Recombee Is the Best Alternative to Amazon Personalize](https://www.recombee.com/vs/amazon-personalize.md): Recombee is a flexible solution for companies that want to have full control over their recommendations and deliver personalized user experience real time. ## Guides & Research - [A Step-By-Step Guide to Integrate Recombee Recommendation Engine](https://www.recombee.com/handbook/download-a-step-by-step-guide-to-the-fastest-integration-eyw34h56k2hu56sh.md): Guide for the simplest form of integration using a No-Code widget. Minimum coding involved. - [Guide: Advanced Media Content Setup for Recombee Recommendation Engine](https://www.recombee.com/handbook/download-content-recommendations-35kl362g0946239g0er.md): Guide for the most popular recommending use cases in VOD, news portals, music industry, and many more. - [Guide: Advanced Product Personalization Engine Recombee](https://www.recombee.com/handbook/download-product-recommendations-dfh09362my2ld4kl32l.md): Guide for the most popular recommending use cases in e-commerce, real estate, marketplaces, and many more. - [Modern Recommender Systems](https://www.recombee.com/handbook/modern-recommender-systems.md): Perspectives, Data, and Objectives: Making Recommender Systems Aligned With Users, Business, Product, and Content Goals - [Research](https://www.recombee.com/research.md): At Recombee, we believe in open innovation and collaborative advancement of AI technologies. - [Research Posters](https://www.recombee.com/research-posters.md): At Recombee, we believe in open innovation and collaborative advancement of AI technologies. - [Research Publications](https://www.recombee.com/research-publications.md): At Recombee, we believe in open innovation and collaborative advancement of AI technologies. ## Optional ### Company - [Contact](https://www.recombee.com/contact.md): Information you need to know about Recombee at business@recombee.com or call on +420 604 499 078 - [About Us](https://www.recombee.com/about-us.md): Recombee provides a leading recommendation engine for one-to-one personalization. - [Explore Our Partnership Opportunities](https://www.recombee.com/partnerships.md): Grow your business together with the most advanced recommendation engine on the market. Boost your client’s satisfaction and KPIs with real-time content, product and search personalization. - [Careers at Recombee | Be part of AI revolution](https://www.recombee.com/jobs.md): Recombee is an AI-powered recommendation engine. We are helping our clients to reach their KPIs by applying the newest machine learning and AI algorithms. - [Backend Developer — Python | Careers at Recombee | Be part of AI revolution](https://www.recombee.com/jobs/backend-developer.md): Recombee is an AI-powered recommendation engine. We are helping our clients to reach their KPIs by applying the newest machine learning and AI algorithms. - [Business & Communications Specialist | Careers at Recombee | Be part of AI revolution](https://www.recombee.com/jobs/business-and-communications-specialist.md): Recombee is an AI-powered recommendation engine. We are helping our clients to reach their KPIs by applying the newest machine learning and AI algorithms. - [Growth Marketing Specialist / Growth Engineer | Careers at Recombee | Be part of AI revolution](https://www.recombee.com/jobs/growth-marketing-specialist.md): Recombee is an AI-powered recommendation engine. We are helping our clients to reach their KPIs by applying the newest machine learning and AI algorithms. - [Sales Manager / Strategic Account Executive | Careers at Recombee | Be part of AI revolution](https://www.recombee.com/jobs/sales-manager.md): Recombee is an AI-powered recommendation engine. We are helping our clients to reach their KPIs by applying the newest machine learning and AI algorithms. ### Legal - [Terms of Service](https://www.recombee.com/terms-of-use.md): Read Recombee's Terms of Service. - [Cookies](https://www.recombee.com/cookie-policy.md): At Recombee we respect individuals’ rights to privacy and value the relationship with customers. Hence, below we provide information about our cookie policy. - [GDPR Compliant Recommendation Engine](https://www.recombee.com/gdpr.md): GDPR is the most important change in data privacy regulation in 20 years and Recombee strongly adheres to its policy. - [Privacy Policy](https://www.recombee.com/privacy-policy.md): Read Recombee's Privacy Policy.