Intro D→D D→C C→D C→C
Find your tribe. Borrow their wins.
Similarity Method
Expert-curated templates → deterministic hash

QIS Protocol: Quadratic Intelligence Scaling

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EMR/Registry
☁️
VectorDB
Network Baseline
Struggling
Thriving
Agents (N): 50
Synthesis Θ(N²): 1,225
Speed 1x
All architectures covered under 39 provisional patents

Four Architectures, Same Θ(N²) Scaling

Metric D→D (Edge→DHT) D→C (Edge→VectorDB) C→D (EMR→DHT) C→C (EMR→VectorDB)
⚡ Parallel Queries Unlimited (decoupled) ~1-10K QPS/cluster EMR-limited; ∞ reads min(EMR, VectorDB)
🔒 Privacy Maximum Moderate High Lower
📤 Data Shared None (edge-only) Vectors only (no PHI/PII) Full data → Registry Full → EMR + vectors → DB
⛓️ Single Point of Failure None Provider Publisher only Full
⚡ Real-time Yes (P2P gossip) Near (API latency) Yes (post-publish) Batch/Near
🔄 Routing O(log N) DHT hops O(1) server call O(log N) DHT hops O(1) server call
🌍 Scale Ceiling Billions (BitTorrent-class) High (pagination) Billions High (sharding)
💰 Cost Bandwidth only Storage + queries Minimal Highest
📊 Synthesis Fully P2P Edge or serverless Edge swarm Client/serverless
All four architectures achieve Θ(N²) quadratic intelligence scaling.
Key differentiators: privacy, real-time propagation, and fault tolerance. D→D offers maximum privacy with zero data sharing and no single point of failure—ideal for sensitive, real-time use cases. Other architectures trade these for operational simplicity, suiting different industries and requirements.
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PLANETARY INTELLIGENCE ACHIEVED
You Just Witnessed 50 Nodes. Now Imagine Billions.
50
Nodes Today
∞
Domains Tomorrow
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