Join innovative organizations using Synerise Platform and explore hundreds of low code use cases
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Why Synerise?

One Platform. Infinite potential.

A single, unified environment that brings data, intelligence, and automation together — powered entirely by proprietary Synerise technology. Built for scale, security, and real-time learning — from infrastructure to AI.
Behavioral Data Hub

Behavioral Data Hub

Absorb & Transform Behavioral Profiles In Real Time and at Any Scale

The proprietary Terrarium™ data engine continuously captures, processes, and enriches behavioral data into living, evolving profiles. Each signal becomes part of a dynamic identity graph — enabling instant insight, personalization, and prediction.
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Artificial Intelligence Hub

Artificial Intelligence Hub

Understand, Infer & Predict Behavior With the World’s Most Advanced AI Model

Synerise AI Hub is powered by the award-winning behavioral foundation model — built to interpret signals, predict intent, and generate insights across any dataset. It learns continuously, adapting its reasoning to every new context.
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Automation Hub

Automation Hub

Orchestrate Intelligence Across Systems And Act with Speed and Precision

A powerful workflow engine designed to automate decisions, synchronize data, and execute context-driven actions. It connects every part of your ecosystem into one adaptive automation layer.
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Decision Hub

Decision Hub

Measure, Simulate & Optimize Outcomes With Continuous, Data-Driven Intelligence

Decision Hub turns behavioral data and AI predictions into clear strategies. Analyze performance, forecast scenarios, and refine operations — all from one real-time control layer.
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Data Modeling Hub

Data Modeling Hub

Define, Evolve & Govern Your Data Models Without Complexity or Downtime

Our Schema Intelligence Layer lets you build and evolve data models in real time — without migrations or downtime. Adapt structures as your ecosystem grows, maintaining a single source of truth for every entity, object, and relationship.
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Experience Hub

Experience Hub

Deliver Context-Aware Interactions Across Every Channel and Touchpoint

Send messages that adapt to behaviors in real time. Communication Hub merges automation with personalization, turning every interaction — from email to in-app — into a seamless behavioral experience.
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Discover an intelligence platform to understand and act — at any scale.

Synerise connects data, AI, and automation to interpret behavior, predict outcomes, and drive action across people, systems, and environments.
Integrate data

Seamlessly Integrate Every Data Source

Bring all your behavioral, operational and contextual data together — automatically, securely, and in real time. Synerise integrates signals from mobile, web, physical sensors, third-party systems and more to build a unified behavioral data foundation.
Products
Offers
Click Streams
Calls, Surveys & Chat Logs
Online & POS Purchases
Behavioral Profiles
3rd Party Systems
Weather Data
Locations
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Unify Information

Bring behavioral profiles and actions together in one intelligent view

Combine interactions, transactions, attributes and activities into one evolving profile — whether that’s a person, a process or an object. Synerise offers unified profile views, policy control and dynamic attributes.
Consent management
Unified profile view
Profile merging
Loyalty programs
Real-time direct messaging
Deep analytics (LTV, CLV, RFM)
Policy control
Dynamic attributes
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Manage Data & Control Access

Secure, govern, and empower data collaboration

Built for scale and compliance, this layer allows you to manage who can access what, via APIs, streaming data and custom objects — ensuring governance doesn’t slow you down.
API access
Catalog management
Stream events manager
Self-service data importer
Custom objects
Advanced role filtering
ACL & password policies
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Analyze Lifetime Data Streams

Turn every event into actionable intelligence

Go beyond dashboards to discover how people, teams or systems evolve over time. Understand flows, segment behavior, uncover churn or retention — in real time.
Attribution modeling
Metrics
Dynamic segmentation
Funnels
Histograms
Trends
Sankey diagrams
Churn analytics
Reporting & dashboards
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Predict, Decide & Personalize

Use AI to understand, anticipate, and deliver what’s next

Harness machine learning to predict intent, recommend content, and personalize experiences — automatically and at scale.
Scoring
AI-driven recommendations
Price & assortment logic
Personalized offers
Time optimization
AI search
Propensity modeling
Automatic insights
Predictions
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Automate, Optimize & Execute

Coordinate intelligent actions with precision and scale.

Build adaptive workflows, synchronize systems, and deliver personalized experiences that evolve with every interaction.
A/B/X testing
Data transformations
External system synchronization
Workflow automation
Content studios
Service prioritization
Autonomous scenarios
Contextual messaging
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Deliver Content & Activate Profiles

Omnichannel Communication

Reach every behavior, in every channel — with context-aware, real-time intelligence that adapts to every moment of interaction.
SMS
Email
Mobile Push
Web Dynamic Content
In-App
External Apps & POS
Social Networks
Ad Networks
Locations
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Create, Connect & Extend Features

Custom Extensions, APIs & Dedicated Portals

Extend your ecosystem with enterprise-grade tools built for flexibility, speed, and security.
Registration as a Service
Login as a Service
Unified API Access
Templates & Cookbooks
SAML
Design System
Hot & Cold Storage Access
SDKs & Webhooks
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Case studies

From data to decisions. From decisions to competitive advantage.
Global scale

The backbone for behavioral intelligence

Synerise powers real-time data, AI, and automation at planetary scale — enabling organizations to understand and act on behavior across people, systems, and environments. From a single signal to billions of decisions every day, our infrastructure is built for speed, trust, and continuous learning.

3k

Active operators on the Synerise platform

33%

Customers are self-serviced

67%

Customers are served by Partners

70+

Active Partners worldwide (e.g., EY, Accenture)

850

Synerise Certificate issued

460+

Production Workspaces (instances)

200

Organizations

49

Countries from 6 continents (>150 with Cleora.ai)

~6B

Behavioral profiles scanned daily

35B

API calls per month

17.5B

Decisions in workflows per month

1.8B

Hyper-personalized messages sent per month

2.9K

Synerise application pods (19.6K all app pods)

~30K

AI decisions per second at peak

~28K

API calls per second at peak

1.2B

Unique dynamic content generated per month

124TB

Data sent via API per month

~1B

Mobile view events collected per month (auto tracking off)

4.64B

AI recommendations, searches, and predictions per month

2.2B

Page visit events collected per month

>140B

Queries to the Terrarium DB per month

42B

Events collected per month

42B+

Rows in Postgres clusters

16400

Kubernetes pods

750+ TB

Disk size

890+

Kubernetes nodes

420+

VMs

2

Cloud providers (Azure, GCP)

71+ TB

RAM

14400+

vCPU

3

Production SaaS deployments

114

Database clusters

150B EUR

GMW processed annually
BaseModel.ai

Apply science to behavioral data. Automatically.
Get answers for all crucial questions.

Reduce your modeling life-cycle to days instead of months

General

How do daily customer interactions influence their future behaviors?

Retail

How much will the customer spend in a specific category next week?

Travel

What is the customer’s expected number of trips this year?

Customer Service

What is the customer’s likelihood of using a special offer?

Telco

How much data traffic will the customer use this month?

Health

How many diagnostic tests will the patient need this year?

Insurance

How many insurance policies will the customer subscribe to this year?

Gaming

How many power-ups/bundles will the gamer buy this month?

Banking

What is the customer’s projected profitability in the next quarter?

Ecommerce

Which products/promotions/ offers/categories the customer is interested in?

Home & Furniture

How to split the customer population into behaviorally distinctivegroups?

Automotive

What kind of product/category is the customer interested in and why?

Software

Will the customer churn in the near future and what events had an impact on that?

Payments

What is the utility of customer for your business and what arethe behavioral and sociodemographic factors affecting it?

Fashion

Will the customer make a purchase next week? Whatsteps need to be taken to increase the chance of purchase?

Security

Is recent behavior of the customer inconsistent with past habits?

Compliance

Are there outlier customers in the population, who might be worth looking into?

News & Publishing

Will the reader subscribe to a premium plan?
Simple. Fast. Powerful.

Cleora

General-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.
Science

Lab

Sair is a lab focused on behavioral modeling, recommendations, large-scale data and graphs processing. We share our ideas, models, and experimental results, also presenting our take on important breakthroughs and interesting technologies. We hope to build a better and more thorough understanding of the field. We believe in the importance of this research not only from a business perspective but most importantly as a study of human decision-making processes.
Research
8 min read

BaseModel vs TIGER for sequential recommendations

The comparison between BaseModel and TIGER reveals substantial differences in their architectural choices and performance.
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Research
8 min read

BaseModel vs HSTU for sequential recommendations

To evaluate BaseModel against HSTU, we replicated the exact data preparation, training, validation, and testing protocols described in the HSTU paper.
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Research
8 min read

Fourier Feature Encoding of numerical features

Pre-processing raw input data is a very important part of any machine learning pipeline, often crucial for end model performance
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Future
6 min read

Why We Need Inhuman Artificial Intelligence

We continuously wonder how much longer it will take until AI reaches human skill level in these tasks - or, when does AI become "truly" intelligent.
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Engineering
12 min read

EMDE vs Multiresolution Hash Encoding

When we created our EMDE algorithm we primarily had in mind the domain of behavioral profiling.
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Tools
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Efficient integer pair hashing

Mental models are simple expressions of complex processes or relationships.
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Research
9 min read

Cleora: how we handle billion-scale graph data

We have recently open sourced Cleora — an ultra fast vertex embedding tool for graphs & hypergraphs.
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Research
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Towards a multi-purpose behavioral model

In various subfields of AI research, there is a tendency to create models which can serve many different tasks with minimal fine-tuning effort.
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Research
10 min read

EMDE Illustrated

In this article we provide some intuitive explanations of our objectives and theoretical background of the Efficient Manifold Density Estimator (EMDE)
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Research
7 min read

How we challenge the Transformer

Having achieved remarkable successes in natural language and image processing, Transformers have finally found their way into the area of recommendation.
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We are sharing our ideas with others!

Our research papers based on Synerise BaseModel.ai framework
Multidimensional Hopfield Network
Redefining Graph Clustering: A Convergence of Algorithms and Networks
A Foundation Model for Behavioral Event Data
SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023
Real-Time Multimodal Behavioral Modeling
CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
An Efficient Manifold Density Estimator for All Recommendation Systems
International Conference on Neural Information Processing (ICONIP 2021)
Cleora: a Simple, Strong and Scalable Graph Embedding Scheme
International Conference on Neural Information Processing (ICONIP 2021)
Twitter User Engagement Prediction with a Fast Neural Model
15th ACM Conference on Recommender Systems RecSys Challenge Workshop, 2021
Node Classification in Massive Heterogeneous Graphs
ACM's Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) KDD Cup Open Graph Benchmark (OGB) Challenge Workshop, 2021
Efficient Manifold Density Estimator for Cross-Modal Retrieval
The 43th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) eCom Workshop, 2020
Modeling Multi-Destination Trips with Sketch-Based Model
14th ACM International Web Search and Data Mining Conference (WSDM) WebTour Workshop on Web Tourism, 2021
On the Unreasonable Effectiveness of Centroids in Image Retrieval
International Conference on Neural Information Processing (ICONIP 2021)
Interpretable Efficient Multimodal Recommender
Thirty-seventh International Conference on Machine Learning (ICML) Machine Learning for Media Discovery (ML4MD) Workshop, 2020
Temporal graph models fail to capture global temporal dynamics
We propose a trivial optimization-free baseline of "recently popular nodes" outperforming other methods on all medium and large-size datasets in the Temporal Graph Benchmark.