# Scalability Solutions

To handle projected growth to 1M+ daily users, we've implemented:

Horizontal Scaling:

* AI inference sharding across 8 geographic regions
* Elastic Kubernetes clusters auto-scaling to 500+ pods
* State channel technology for prediction delivery

Layer 2 Optimization:

* Batch prediction updates via Polygon zkEVM
* Data availability sampling (Celestia integration)
* Plasma cash framework for historical data

Decentralized Infrastructure:

* 200+ node operators for model training
* Arweave-based model version archive
* Threshold signature schemes for distributed computation

Performance benchmarks show:

* 99.9% uptime at 10,000 RPS
* Linear scaling costs ($0.0001 per additional user)
* Sub-100ms latency across all regions
