Synerise

About the Company

Synerise specializes in using AI and Big Data to transform business insights into actionable strategies. The company offers a cutting-edge Behavioral AI Infrastructure that empowers organizations to predict behaviors and make data-driven decisions. Synerise builds every layer of its AI infrastructure from scratch, ensuring no dependency on third-party AI, databases, or cloud vendors. The company's proprietary technology allows for real-time predictions, personalization, and automation at an enterprise scale.

Products, Services & Tech Stack

Core Solutions

• Behavioral Data Hub: Absorbs and transforms behavioral profiles in real time and at any scale.
• Data Modeling Hub: Offers a unified data layer for real-time ingestion and analysis.
• Predictive Inference & Recommendation Models: Applies supervised and self-supervised learning for intent inference and item-level recommendations.
• Orchestration & Adaptive Workflow Execution: Composes multi-step workflows with conditional branching and system synchronization.
• Content & Activation Profiles: Dispatches behavioral interventions across multiple channels with context-aware selection and frequency optimization.

Technologies & Frameworks

• Proprietary AI Infrastructure: Built in-house from TerrariumDB to BaseModel.ai.
• Real-Time Processing: Capable of handling 31 billion events per month with sub-millisecond latency.
• Scalability: Designed to scale linearly with horizontal scalability.
• Security: ISO 27001 certified, GDPR compliant, and SOC 2 certified.

Project Scope & Target Clients

Client Base

• Retail: Empik, Las Tijeras Mágicas, MIG Marketing Investment Group, Modivo
• Fashion & Sport: Nike Chile
• Telco: Orange
• Banking: BNP Paribas
• E-Commerce: Minimalism

Engineering Scale

• Global Scale: Powers real-time data, AI, and automation at planetary scale.
• Performance Metrics: Handles 31 billion events per month, 90 billion queries to the TerrariumDB per month, and 3.8 billion AI recommendations, searches & predictions per month.
• Infrastructure: Operates on a Kubernetes cluster with 16,400+ pods, 750+TB disk size, 890+ nodes, 420+ virtual machines, 71+TB RAM, and 14,400+ vCPU.