Truly Individualized Item Recommendations
Compared to most recommendation engines deployed today, Crossing Minds models don’t cluster individuals in buckets of hundreds of thousands of users. Instead, Crossing Minds’ recommendations are truly tailored to each profile.
Time Decay & Taste Evolution
Compared to most recommendation engines deployed today. Instead, Crossing Minds’ recommendations are truly tailored to each profile, factoring in nuances like the relationship between time and preference.
Behavior-Based Recommendations & Database Transfer Learning
The vast majority of online browsing occurs without any long-term user identifier, hence being able to deploy behavior-based recommendations in seconds - not hours - is critical to remain relevant. Additionally, our platform is capable of on-the-fly transfer learning and predictions.
Runtime Efficiency in Production
Our API leverages a blazingly fast proprietary nearest neighbor tree index and database. Most recommendation APIs lack this combined expertise and often rely on off-the-shelf database technologies instead, limiting what they can deploy to overly simplistic models.
Crossing Minds’ API does not limit the available filters to only a few selected ones for a particular vertical. Instead, customers can create their own properties and attributes and modify them at any time, allowing for custom business rules to control the recommendations.
The Crossing Minds solution integrates with key CDPs and PaaS, including but not limited to Segment, mParticle, and BigQuery. With just a few clicks, customers can feed their users’ events directly into the Crossing Minds API without writing any code.
Crossing Minds' API automatically re-trains the recommendation following event-based triggers. This means that each and every time your database changes significantly, the entire model is re-trained from scratch.