GEO_LOCAL_AGENT_MESH
Spatial pub/sub for AI agents — discover peers and context by physical proximity
Autonomous agents — coordinated AI copilots, multi-agent workflows, ambient assistants — need to find peer agents and live context with the locality that physical proximity implies. Today that lives behind centralized APIs that throw away geography. Hyperweave gives every agent a Hilbert position, makes 'find agents/data within 50 km' a native query, and propagates state changes via Merkle-digest anti-entropy in O(log n) rounds. No central knowledge base, no per-app sync server.
Multi-Agent Context Network
AI agents collaborating and fetching live context from distributed data sources through Hyperweave mesh
ORCHESTRATOR
L5QUERIES
0
SOURCES
5
FRESH
98%
NETWORK_LOG
AGENT_TYPES
DATA_FLOW
SPATIAL_PUB_SUB
Agents publish interest at their geographic cell; providers subscribe at nearby cells. Rendezvous anchors at √n positions make 'find peers within X km' a single-shot query — matchmaking p50 is bounded by same-region routing latency.
DISTRIBUTED_AGENT_MEMORY
Agent conversation history, learned preferences, and tool results are CAS records replicated to nearby cells. Hand-offs between edge nodes preserve continuity without a central session store, and every replica is signed against the agent's Ed25519 identity.
MERKLE_DIGEST_KNOWLEDGE_SYNC
Knowledge updates propagate via 1 s Merkle-digest anti-entropy. When a fact changes upstream, nearby agents converge in O(log n) AE rounds — no central knowledge base to invalidate, no cache coherence policy to tune.
MULTI_AGENT_DISCOVERY
Capability filter (model loaded, tools available) + spatial filter (within radius) + tier filter (compute-tier 4–6) = a single Hyperweave discovery query. Agents delegate tasks to the right peer by structure, not by hard-coded directory.
Context query
4.65× faster vs top DHTs
Tail latency (p99)
5× faster vs top DHTs
Agent discovery
O(log n) via Hilbert-fingers
Knowledge TTL
Configurable
Target scale
1M peers
Data sources
Any mesh node
Contextual Awareness
Agents access real-time local context—weather, traffic, events—from the nearest data sources. No stale cached data, no central database bottleneck.
Agent Collaboration
Specialist agents handle domain-specific tasks while coordinators orchestrate complex workflows. All communication happens through the secure mesh.
Persistent Memory
Agent memories replicate across geographic regions. Users maintain conversation context even when connecting from different locations.