INTELLIGENT_AI_AGENTS
Context-Aware AI with Live Data Access
AI assistants that pull live context from nearby sources instead of stale central databases. Faster, fresher answers without the bandwidth bill through Hyperweave's geographic mesh routing.
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
CONTEXTUAL_DATA_FETCHING
AI agents query the nearest data sources first. Need local weather? Traffic? Inventory? The mesh routes queries to geographically relevant nodes, not distant central servers.
DISTRIBUTED_MEMORY
Agent conversation history and learned preferences are replicated across nearby mesh nodes. Users get consistent experiences regardless of which edge node handles their request.
REAL_TIME_KNOWLEDGE_SYNC
Updates propagate through the mesh via gossip protocol. When a fact changes, all nearby agents learn within milliseconds—no central knowledge base bottleneck.
MULTI_AGENT_COORDINATION
Agents can discover and communicate with other agents in the mesh. Delegate tasks, share insights, and collaborate without human orchestration.
Context Query
< 15ms
Memory Sync
< 50ms
Agent Discovery
< 20ms
Knowledge TTL
Configurable
Concurrent Agents
Unlimited
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.