Recommendations Engine - Data Machines
by People Tech Group Inc
AI powered recommendation engine for superior recommendations with built-in monitoring and analytics
Providing contextual recommendations to users of technology platforms such eCommerce apps, Content apps, eLearning apps, Social Media apps and any other applications that will benefit for continued user engagement
Eliminate the overhead of implementing traditional complex Machine Learning based implementations
Ability to provide Real Time recommendations based on user actions (Ex. Providing recommendations upon login/ When product is viewed/ Performing a Search Action/ During Support Interactions)
Avoid delayed or irrelevant recommendations by learning from User Activity in as little time as 15 minutes to provide immediate recommendations for active users.
How the challenges are being addressedBy integrating real-time data ingestion to continuously gather all relevant user activity data
Automatically building a database consisting of all objects suitable for recommendations
Multi-channel support – consistent user experience across all audiences/implementations
Fully secure, physically, and logically isolated, with data encrypted in transit
Product HighlightsBuild your own recommendation engine in minutes
Recommend products, videos, music, books, job postings, etc. based on user activity
Multi-Tenant platform that can enable B2B applications to provision automatic recommendations to multiple clients with their own secure Recommendation AI model
Self learning model to provide Context based recommendations or Action based recommendations
Real-Time observability and governance to observe recommendations being provided to users in real time or analyse historic data to review past recommendations
Ability to correlate recommendations with user activity to assess effectiveness of recommendations (Additional Feature)
Simplified integration with your data and user experiences
Multi-lingual support
Self-learning, continually enhanced recommendations
Fast, operates at scale and in real-time
Built-in monitoring dashboards and insights