AI That's Private
Run models anywhere, train collaboratively, verify everything. Privacy-preserving AI infrastructure for the next generation of applications.
The Problem withCurrent AI Infrastructure
Traditional AI platforms require sending data to centralized servers, creating privacy risks, compliance challenges, and vendor dependencies. There's a better way.
Current Challenges
Data Privacy Concerns
Current AI requires sending sensitive data to centralized servers, creating privacy risks and compliance challenges
Vendor Lock-in
Dependence on API providers creates ongoing costs, service disruptions, and loss of control over AI capabilities
Limited Collaboration
Organizations can't train AI together without exposing proprietary data, slowing innovation and improvement
Tenzro Solution
Private Execution
Run AI models in browsers, mobile apps, servers, or TEEs without exposing data to third parties
Collaborative Learning
Train models together across the network using federated learning without sharing raw data
Verified Intelligence
Cryptographic proof of model provenance and execution integrity through TEE attestations
Complete Privacy-Preserving AI Infrastructure
Tenzro combines private execution, collaborative learning, and cryptographic verification into a complete framework for building privacy-first AI applications that work across browsers, mobile devices, servers, and TEEs.
Four CoreCapabilities
Tenzro enables private AI at global scale through execution, collaboration, orchestration, and verification.
Private Execution
Run AI Without Exposing Data
Execute AI models in browsers, mobile apps, servers, or TEEs. Process data locally with WebGPU acceleration, works offline, no API costs after download.
Collaborative Learning
Train Together, Keep Data Private
Federated learning enables training AI models across the network without sharing raw data. Differential privacy, secure aggregation, and TEE attestation ensure privacy.
Orchestration
Multi-Model Coordination
Coordinate multiple AI models working together for complex workflows. Route requests intelligently, chain outputs, manage agents, and optimize resources.
Verified Intelligence
Cryptographic Proof of AI
TEE attestations and blockchain verification provide cryptographic proof of model provenance, training contributions, and execution integrity.
Why Privacy Matters
Data Sovereignty
Users keep control of their data. No centralized servers storing sensitive information.
Regulatory Compliance
Meet GDPR, HIPAA, and other privacy requirements through private local execution.
Zero Vendor Lock-in
Models run locally. No ongoing API costs or service dependencies.
Real-WorldApplications
From ecommerce to healthcare, Tenzro enables privacy-preserving AI across industries.
Ecommerce
Personalized recommendations without tracking individuals. Model runs in customer's browser, trains on local behavior, contributes to collaborative model. Merchant gets aggregate insights without storing PII.
Example: Platform improves autonomously - more shoppers create better recommendations, attracting more customers in a self-reinforcing cycle
Framework for BuildingComplete AI Platforms
Tenzro provides the infrastructure for creating complete AI platforms and standalone apps with their own ecosystems, agents, and autonomous improvement systems.
Multi-Model Orchestration
Coordinate multiple AI models working together for complex workflows
Agent-Based Systems
Build autonomous agents that can plan, reason, and execute tasks
MCP Integration
Connect to Model Context Protocol for enhanced knowledge access
RAG Systems
Retrieval Augmented Generation with private knowledge bases
Data Flywheels
Self-improving systems that get better with usage
Autonomous Training
Automated retraining loops without manual intervention
Example Platforms Built on Tenzro
DAML Studio
AI-powered smart contract generation platform
AI Film Studio
Creative production workflows with multi-model coordination
Custom Platforms
Build your own AI platform with complete ecosystem
Self-Improving AI Systems
Build platforms that automatically improve through data flywheels and reinforcement learning. Models get better with usage while preserving privacy through federated learning and differential privacy.
Built forPerformance and Privacy
Enterprise-grade infrastructure with cryptographic privacy guarantees and high-performance execution.
Execution Environments
Model Support
Network Performance
Privacy Protection
Build Privacy-First AIApplications Today
Join developers, businesses, and researchers building the future of private, collaborative, and verifiable AI.
Private • Collaborative • Verified