Cutting-edge AI-driven infrastructure tailored for collecting, analyzing, and interpreting behavioral data. By leveraging the power of AI and machine learning, we transform raw behavioral data into actionable intelligence, enabling organizations to make data-driven decisions with unprecedented accuracy and efficiency.
Efficient Manifold Density Estimator is a framework utilizing arbitrary vector representations with the property of local similarity to succinctly represent smooth probability densities on Riemannian manifolds.
Built for developers, data engineers, data scientists.
Ultra-fast disk & in-memory column & row store engine designed specifically for real-time heterogeneous data collection & processing, behavioral intelligence, data management & execution of various business scenarios at scale.
Dailymotion.com has applied EMDE/BaseModel.ai to personalize video recommendations in native applications, leading to improved relevance and catalog coverage
EMDE (BaseModel.ai) gives us a generalised framework for recommendations. The embedding generation was superfast (i.e <5 minutes). For context, do remember that GraphSAGE took ~20hours for the same data in the NCR region.
BaseModel.ai is core for all AI services offered in Synerise platform
BaseModel’s powerful behavioral analysis enables us to make sure that our clients receive communication tailored specifically to their preference.
Unified Synerise Experience Platform
A fully integrated suite of behavioral intelligence products
We created an end-to-end experience & continuous intelligence framework - connecting modern data collection, processing methods & analytics with AI-driven business scenarios execution.
Heterogeneous data sources integration
Products & offers
Calls, surveys & chats logs
Online & POS Purchases
3rd party data
Behavioral profiles & actions in one place
Unified Profile View
Profile Merging policy
Deep Analytics (LTV, CLV,RFM)
Expressions & Dynamic Aggregates
Manage Data & Controll Access
Security by design
ACL & Password policies
Data self-service importer
API Access Management
Stream Events Manager
Analyze lifetime data streams
Actionable & advanced analytics & BI
Histograms & Trends
Reporting & Dashboarding
Predict, decide & personalize
ML & deep learning supported decisions
Price & Assortment Logic
Automate, Optimze & Execute
External System Sync
Deliver content & activate profiles
Web Dynamic Content
External Apps & POS
Create, connect and extend features
Custom extensions, APPs & dedicated portals
Registrationas a Service
Login as a Service
Unified API Access
Templates & Cookbooks
Hot & Cold storage access
SDKs & Webhooks
Synerise is able to track every event, across every channel, for the customer - whether it's mobile, it's web, it's retail, physical presence.
All of that is signal that's being continuously collected, processed, and then in turn AI is being applied, workflows are being applied to drive the experience
Satya Nadella about Synerise
Apply science to behavioral data. Automatically. Get answers for all crucial questions.
Reduce your modeling life-cycle to days instead of months
How do daily customer interactions influence their future behaviors?
How much will the customer spend in a specific category next week?
What is the customer’s expected number of trips this year?
What is the customer’s likelihood of using a special offer?
How much data traffic will the customer use this month?
How many diagnostic tests will the patient need this year?
How many insurance policies will the customer subscribe to this year?
How many power-ups/bundles will the gamer buy this month?
What is the customer’s projected profitability in the next quarter?
Which products/promotions/ offers/categories the customer is interested in?
Home & Furniture
How to split the customer population into behaviorally distinctivegroups?
What kind of product/category is the customer interested in and why?
Will the customer churn in the near future and what events had an impact on that?
What is the utility of customer for your business and what arethe behavioral and sociodemographic factors affecting it?
Will the customer make a purchase next week? Whatsteps need to be taken to increase the chance of purchase?
Is recent behavior of the customer inconsistent with past habits?
Are there outlier customers in the population, who might be worth looking into?
News & Publishing
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Simple. Fast. Powerful.
General-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.