DaaN is the distributed compute network that splits AI models across consumer GPUs, Apple Silicon, enterprise hardware, and cloud -- making powerful AI accessible to everyone without centralized infrastructure.
Real-time visualization of the distributed inference grid. Consumer GPUs, Apple Silicon, enterprise hardware, and cloud nodes working together to serve AI requests.
Distributed inference nodes powering AgentOS workflows across global infrastructure
From request to response in milliseconds -- distributed across a global compute grid.
An AI agent submits an inference request. The Ingest Router evaluates complexity, model requirements, and available compute capacity.
The model is split into layers and distributed across the best available nodes. Embedding layers might run on a consumer GPU while attention heads process on Apple Silicon.
Shards execute in parallel across the network. Cross-node communication uses encrypted channels (WireGuard, mTLS, AES-256-GCM) with sub-5ms latency.
Results are aggregated, validated, and encrypted end-to-end before delivery. No single node ever sees the complete model or full response.
From a gaming PC in Austin to an H100 cluster in Ashburn -- every device contributes to a unified inference grid.
Handles embedding layers, token mixing, and lightweight inference tasks. Perfect for community contributors who want to earn compute credits.
Excels at attention head processing and KV cache with unified memory architecture. High memory bandwidth enables large context windows.
Handles the heaviest workloads: FFN blocks, large KV caches, and multi-billion parameter layers with NVLink interconnect.
Elastic overflow capacity for peak demand. Normalization, output heads, and burst inference scaling. Pay only for what you use.
No single node sees the full model or complete response. Every connection uses credit-card-level encryption. No exceptions.
All ingress traffic encrypted with the latest TLS standard
Lightweight VPN tunnels for consumer GPU communication
Protocol-level encryption optimized for Apple device connections
Mutual TLS with certificate pinning for enterprise hardware
Military-grade encryption for intermediate computation results
IPsec tunnels for AWS, Azure, and GCP cloud node connections
High-performance authenticated encryption for node-to-node traffic
End-to-end encryption ensures only the requester can decrypt results
A fundamentally different approach to AI infrastructure that benefits everyone -- from individual contributors to Fortune 500 enterprises.
Anyone with a GPU can contribute compute to the network and earn credits. Powerful AI is no longer reserved for companies with million-dollar infrastructure budgets.
By distributing workloads across heterogeneous hardware, organizations avoid massive centralized GPU cluster costs while maintaining enterprise-grade performance.
No single point of failure. If a node goes offline, the orchestrator automatically redistributes shards to healthy nodes with zero downtime.
From 7B parameter models on a single consumer GPU to 70B+ models sharded across dozens of nodes -- the network scales to fit the model, not the other way around.
Choose where your data is processed. Pin workloads to specific geographies or hardware types. Air-gap sensitive operations to on-premise nodes only.
Optimized routing, intelligent caching, and proximity-aware shard placement ensure inference latency stays under 5ms for most operations.
Contribute your hardware. Access powerful models. Build the future of decentralized AI infrastructure -- together.