We're pioneering the next generation of AI infrastructure —
combining federated learning with cutting‑edge LLMs to revolutionize how models are trained and deployed in Europe.
Challenges
US and China Centric Models and Clouds
US and China Centric Models and Clouds are controlling European AI development and Data, leaving EU's competitiveness at risk.
SYNNQ Pulse interconnects existing and future AI hardware, opening access to enterprises with their AI ambitions to the first federated EU Hyperscaler.
Privacy-by-Design
SYNNQ's privacy‑by‑design, pan‑European AI backbone is built to comply with the EU-AI Act, reclaiming data autonomy, ensuring regulatory alignment, and strengthening strategic independence.
Core Technologies
Federated Learning
Decentralized training on client devices
Large Language Models
Advanced AI for NLP, vision, and multimodal use cases
Inference APIs
Unified endpoints for text, image, audio, and video AI
Opportunities
Global GPU Market
$100B+Utilization
30%Market Growth
Projected 25% CAGR through 2025
Turning an EU Problem into Our Advantage
We tap into Europe's unused compute capacity (~30% idle) across academia, industry, and institutions. Federated training of EURO‑STACK LLMs happens locally—no data export. Europe's strict regulations (GDPR/DSGVO) become a competitive edge. Diverse data sources enhance model robustness and contextual intelligence. Customer data is trained on local nodes leaving data at its source. Compliance instills trust, trust is rewarded with high quality data. HQ data leads to better models. Better models lead to more participation. More participation leads to best in class inference.
Privacy‑first
Only model updates travel—raw data never leaves local devices.
90% Lower Cost
Utilize idle European GPUs instead of expensive hyperscalers.
10× Faster
Model training via our lightweight decentralized architecture.
Built-in GDPR compliance
Auditability & full EU data sovereignty.
Cryptographically secure
Collaborations with distributed‑ledger traceability.
EU-based hosting
Built on European infrastructure with full GDPR compliance and data sovereignty.
Auditability & traceability
Complete transparency in model behavior and training flow for regulatory compliance.
Cryptography integration
Secure, verifiable collaborations between trusted nodes through distributed ledger technology.
Compliant by design
Architected to avoid U.S. CLOUD Act vulnerabilities while meeting EU AI regulations.
A robust, scalable, and secure framework for decentralized machine learning
Federated Learning Core
- Decentralized training: data stays at the edge → only encrypted gradients are shared
- Secure aggregation: cryptographic protocols ensure privacy and compliance
Distributed Training Engine
- 3D parallelism + gradient compression (Top‑K, 8‑bit) + Flash Attention = scalable, efficient performance
- Adaptive communication handles heterogeneous networks smoothly
- Dynamic batch sizing: maximizes GPU utilization in varied environments
Multi‑Model Context Protocol (MMCP)
MMCP allows cross-model communication
Control Plane & Monitoring
Federated orchestration, health dashboards, fault tolerance—all realtime
Overview
This deep dive into our federated learning system architecture, covering server and client components, their interactions, and key features that enable real-time collaboration while preserving data privacy. Our system leverages cutting-edge distributed computing principles to enable secure, efficient model training across a network of devices. The architecture is designed to scale seamlessly from small clusters to global deployments, with built-in fault tolerance and automatic load balancing. Each component is optimized for performance while maintaining strict privacy guarantees, ensuring that sensitive data never leaves its source while still contributing to the collective intelligence of the system.
Security First
- End-to-end encryption
- Authentication & authorization
- Data never leaves the client
- Privacy-preserving aggregation
From healthcare to finance, we've helped organizations transform their AI capabilities while maintaining data sovereignty.
Healthcare
Federated fine‑tuning on patient records (HIPAA/GDPR).
Finance
Secure risk modeling, fraud detection across institutions.
Public Sector
Sovereign LLMs for government agencies—no data leaves jurisdiction.
Enterprise
Contextual adaptation for regional business needs.
Let's build something extraordinary together. Your success is our success.
Harness the power of federated learning with our edge-based transformer architecture, enabling collaborative intelligence while preserving data privacy and security.
Client Software
Autonomous agents that train on local data and contribute to the global model without sharing raw data.
Data Privacy Preserved
Faster Training
Efficient resource utilization across nodes
Secure and reliable connection to central server.
Efficient model training on local datasets
Real-time performance monitoring
Automated resource management
Dashboard access
Real-time updates
Training stats
Resource usage
Developer & HPC Participation – SYNNQ SDK
A powerful Software Development Kit that enables seamless integration of federated learning capabilities into your applications.
Faster Integration Speed
Uptime Guarantee
Built-in encryption and privacy features
Install via package manager with a single command
Simple environment setup with smart defaults
Complete API reference
Step-by-step guides
Real-world use cases
Optimization tips
Active forum and Discord community
24/7 technical assistance
For Developers
SDK/API for federated LLM application development. Install via synnq_fl; includes client/server interfaces, security, logging & monitoring. Rapid integration: 20% faster setup, 99.9% uptime; enterprise‑grade support.
For Compute Providers (HPC/Edge)
Monetize idle GPUs while keeping data in-house. Enforce data sovereignty & auditability via policy‑aware federation. Seamless integration into Pulse's orchestration grid.
Join the Community
Harness the power of our SDK to build your own federated LLM applications or contribute to our growing network. Whether you're a developer looking to integrate federated learning into your existing applications or a researcher exploring distributed AI, our comprehensive toolkit provides everything you need to get started. Join a community of innovators pushing the boundaries of collaborative machine learning.
Outlook & Financing
Roadmap
Q3/Q4 '25 – federated rollout of 7B→230B‑parm EURO‑STACK LLMs.
Funding Goal
€15 M to scale training platform and SDK adoption.
Revenue Channels
API Usage
Enterprise API services
Enterprise LLM Services
Custom model development
Government Deals
"Democracy OS" partnerships
Vision
Become Europe's foundation for secure democracy, public services, and sovereign digital identity.
Our advanced LLM Model powers state-of-the-art language understanding, with specialized layers for enhanced context processing and knowledge integration.
Next big ambitions?
We match the energy.