Netflix currently employs over 300 people with a total spend of over $150 million to maintain and improve their content recommendations.
With our personalised recommendation service, you can provide the right information to the right person at the right time.
The world is moving towards personalisation; it increases customer satisfaction, engagement, experience and sales. As a customer, you are looking for the best deals, whether this is car hire, hotel upgrade or even a flight upgrade. With our recommendation service, you can be sure to receive the right offers at the right time. Our products come fully-equipped with world class machine learning, natural language processing, information retrieval, in conjunction with recommendation technologies such as Collaborative Filtering, Content Based Filtering and Case-Based Reasoning combined using Hybrid Methodology.
As a manager of millions of customers, you want to be consistently increasing sales while retaining current customers. All our products come fully equipped with cutting edge Artificial Intelligence techniques, such as, machine learning, natural language processing, information retrieval, in conjunction with recommendation technologies such as Collaborative Filtering, Content Based Filtering and Case-Based Reasoning combined using Hybrid Methodology.
Recommendation as a Service (RaaS) is a cloud-based API platform which offers real-time recommendations and personalisation. The platform offers a range of recommendation utilities to cater for context-aware, conversational and explanatory scenarios. RaaS enables firms to enhance customer experience across all web, mobile and email, leading to statistically significant increases in conversion rates by 5x, contributing to 29% uplift in revenue.
We design, develop and deploy cutting-edge solutions for large enterprises in various enterprise verticals including Financial Services, Travel and Telecommunications. We work with the most forward-thinking organisations, helping our partners find new levels of efficiency and revenue streams to achieve their strategic goals.
Predictive chatbots, powered by artificial intelligence, questions are interpreted and relevant knowledge base articles, online resources or subject matter experts within the organisation are recommended.
Using A.I. we are applying new disruptive solutions to digitally transform manual processes. We design, develop and deploy cutting-edge solutions for large enterprises in various enterprise verticals.
Using our products, you can successfully generate business ideas, resulting in better informed decisions and driving ancillary sales by identifying the right product, the right person at the right time.
Tool that utilises our solutions with a focus towards B2B2C. Designed to help companies increase sales by utilising recommender systems for their customers, similar to Netflix and Amazon.
Tool that utilises our A.I. solutions and is focused towards B2B. Leveraging our predictive analysis companies can understand customer trends and drive ancillary sales.
At RecommenderX we have some of the brightest minds in the world of recommender systems. Our team is founded in science, we bring together years of experience building and studying recommender systems.
We currently help global banks, governments, and universities to sift through the immense amount of data available to produce actionable insights and recommendations.
We have some great clients, we value their feedback, here is what they have to say
Barry is Professor of Computer Science at University College Dublin where he heads up the INSIGHT Centre for Data Analytics. He has co-founded two companies (ChangingWorlds and HeyStaks), raised 4 rounds of VC investment totaling more than $8m. In 2008 ChangingWorlds was acquired for $60m. He is particularly experienced in bringing IP-rich propositions to the market, and his experience as a senior academic and scientist combined with his startup expertise and business acumen provides a unique perspective on the development of high-potential startups.
Kevin holds a PhD from University College Dublin, and has over 10 years of research experience in the areas of Personalization Technologies and Recommender Systems. He has produced more than 50 peer-reviewed publications and several patents. Kevin has a keen understanding of technology, solution architecture, software development and commercialization and expertise in the areas of data analytics, machine learning and data visualization. He has been developing commercial software for over five years and has designed and overseen the development and deployment of several licensed digital platforms. He is the CTO and a co-founder of RecommenderX.
Data is Mick's passion. Over the last 15 years he has moved from artificial intelligence and information retrieval, through Semantic Web technologies, and on to machine learning and Big Data Analytics. Mick holds a doctorate from the University of Innsbruck, and a masters from National University of Ireland Galway. Mick has published extensively at conferences, workshops, and in selected journals, as well as authoring two text books in the area of Semantic Web Services. He has also chaired standardization groups in both OASIS and TM Forum.