Find where attention
is going.
Before narratives become obvious.
ATTENZA transforms fragmented public information into structured intelligence by detecting how attention forms, accelerates, clusters and evolves across markets.
Live Signal Stream · Simulated Interface Data
12,842
Signals Observed
326
Narrative Clusters
74
Emerging Catalysts
18
Attention Surges
Markets move after attention moves.
Every market begins with information.
A post. A headline. A developer update. A community conversation. A new participant. A sudden change in sentiment.
Individually, these signals often look insignificant. Together, they can reveal where collective attention is beginning to concentrate.
ATTENZA maps that process.
Fragmented information becomes structured intelligence.
ATTENZA continuously transforms public signals into an evolving map of market attention.
Raw Information
01Fragmented public signals enter the network
Signal Extraction
02Meaningful activity is separated from noise
Entity Mapping
03Signals are linked to projects, people and topics
Narrative Clustering
04Related signals converge into narratives
Attention Analysis
05Velocity, sentiment and conviction are measured
Structured Intelligence
06A live, queryable map of market attention
Understanding attention requires more than sentiment.
Attention
Measures the amount of observable attention around an entity, project or narrative.
Connected Variables
Attention has velocity.
Volume alone is not enough.
A topic receiving 100,000 mentions may already be saturated. A smaller narrative accelerating from 100 conversations to 20,000 conversations can be far more informative.
ATTENZA analyzes the direction, acceleration and persistence of attention.
Attention Velocity
+0%
Markets are networks of narratives.
AI Agents
Accelerating- Attention Score
- 91 / 100
- Velocity
- +218%
- Sentiment
- 72% Positive
- Conviction
- HIGH
- Top Catalyst
- Autonomous agent infrastructure adoption
Connected Narratives
Attention doesn't spread evenly.
Different communities often discover, interpret and amplify information at different speeds.
ATTENZA maps social clusters to understand where narratives originate and how they spread across the network.
Signal propagation · hover a cluster
What changed?
Catalyst Detected
Live Scan- Project
- Example Protocol
- Event
- Major ecosystem partnership
- Narrative
- AI Infrastructure
- Attention Change
- +184%
- Velocity
- Accelerating
- Confidence
- High
When a catalyst appears, nearby narratives react. ATTENZA traces the attention change back to the event responsible for it.
The network, readable in real time.
Simulated demo interface data — a preview of the ATTENZA intelligence environment.
| Narrative | Attention | Trend | Velocity | Conviction | Status |
|---|---|---|---|---|---|
| AI Agents | 94 | +218% | High | Accelerating | |
| Tokenized Equities | 86 | +143% | High | Emerging | |
| Compute | 83 | +112% | High | Accelerating | |
| Robotics | 81 | +127% | High | Emerging | |
| Prediction Markets | 78 | +91% | Medium | Growing | |
| Stablecoins | 74 | +34% | Medium | Growing | |
| Crypto AI | 69 | +58% | Medium | Growing | |
| DePIN | 63 | -18% | Medium | Cooling |
The Attention Intelligence Network
Input Layer
L01AI Processing Layer
L02Attention Engine
L03Intelligence Graph
L04Application Layer
L05The objective is not to predict markets with certainty.
The objective is to understand the movement of attention.
Where is the market's attention going?
Intelligence for machines and humans.
Traders
Discover emerging narratives before they become consensus.
Researchers
Explore how narratives form and propagate.
AI Agents
Give autonomous agents structured awareness of market attention.
Builders
Understand where ecosystems and communities are focusing.
Funds
Monitor evolving narratives and catalysts across markets.
Protocols
Understand how the market perceives and discusses your ecosystem.
Attention as machine-readable intelligence.
ATTENZA is designed not only as a human interface, but as an intelligence layer that autonomous systems can query — structured attention data for agents, dashboards and trading systems.
# Request
GET /v1/narratives/emerging
# Response
{
"narrative": "AI Agents",
"attention_score": 91,
"velocity": 2.18,
"sentiment": 0.72,
"conviction": "high",
"status": "accelerating"
}Powering the Attention Intelligence Network
$ATTENZA is the placeholder ticker for the network's utility layer. Network participation does not imply any guarantee of value, returns or performance.
The Attention Intelligence Thesis
ATTENZA explores a simple idea:
Markets are downstream of information, and information is downstream of attention.
Understanding where attention forms, accelerates and migrates can provide a new layer of market intelligence.
Explore the architecture behind the network.
Documentation covering the intelligence models, data pipeline and network design behind ATTENZA.
From observation to autonomous intelligence.
Phase 01
Observation
- Signal ingestion
- Entity extraction
- Narrative clustering
- Attention scoring
Phase 02
Intelligence
- Attention velocity
- Social cluster mapping
- Catalyst detection
- Conviction analysis
Phase 03
Network
- Attention Graph
- Developer API
- AI agent integrations
- Project intelligence
Phase 04
Autonomous Intelligence
- Real-time agent queries
- Programmable signal infrastructure
- Machine-to-machine intelligence
- Open intelligence ecosystem