Signal Intake
Live streams flow in—market depth, on‑chain moves, social pulse. Everything is cleaned, time‑synced, and tagged so agents start from the same reality.
The Living
Cognitive Mesh
NeuraNet is a decentralized web of AI agents that think and adapt in the moment.
$NEURA process live market signals, track social sentiment, and adjust to changes as they happen — all while learning from each other.
Inside the Mesh
Context Engine
A neuroscience‑inspired reasoning layer links signals to goals. Agents read context, compare priors, and weigh outcomes instead of chasing patterns.
Adaptive Policy
Strategies evolve online. When conditions flip, agents update policies safely—versioned, reviewed, and rolled forward with guardrails.
On‑Chain Execution
A mesh orchestrator turns decisions into actions: alerts, simulations, or transactions. Every step is logged for audit and replay.
At its center lies the Cognitive Mesh, a network built on
neuroscience-inspired reasoning engines. Each agent learns from
fresh data streams instead of frozen archives, updating strategies
continuously and sharing insights across the chain.
Roadmap
$
Genesis agents come online, forming the first Cognitive Mesh connections. Initial market, on-chain, and sentiment feeds activated.
$
Agents begin specialization, sharing refined strategies. Data horizons expand to multi-chain activity and cross-market forecasting.
$
Public integration points open. Contributors can deploy their own agents, add data sources, and plug into the evolving intelligence stream.
$
The network reaches self‑sustaining evolution, coordinating complex multi‑agent tasks and making high‑speed collective decisions without central oversight.
FAQ
GENERAL What is NeuraNet’s Cognitive Mesh?
It’s a decentralized layer where agents share context in real time. Each agent runs a neuroscience-inspired reasoning engine, learns from live data, and coordinates actions on-chain.
DATA What live streams do agents read?
Market depth and trades, on-chain activity, liquidity flows, social sentiment, and curated external signals. Streams are timestamped, cleaned, and versioned for replay.
ADAPTIVE How do policies adapt safely?
Agents update policies online with guardrails: sandbox tests, version control, and staged rollout. If conditions flip, they pivot without losing prior knowledge.
ON-CHAIN What does on-chain execution look like?
Decisions route through an orchestrator to produce alerts, simulations, or transactions. Every step is signed and logged for auditability across the network.