Urban Intelligence That Learns

IoT agents correlate sensor streams with historical patterns. Semantic triggers detect anomalies across city infrastructure.

The Problem

Data Deluge

Millions of sensor readings per minute with no semantic layer.

Missed Patterns

Cross-system correlations invisible to siloed monitoring.

Reactive Ops

Issues detected after they impact citizens, not before.

The HatiData Fix

Semantic Triggers

Fire on conceptual anomaly matches across systems.

City Memory

Historical patterns indexed for instant recall.

Cross-System Intelligence

One query spans traffic, utilities, and safety data.

See It in Action

SELECT s.sensor_id, s.location, s.reading,
       semantic_rank(m.embedding, 'water pressure anomaly pipe burst') AS risk
FROM city_sensors s
JOIN_VECTOR infrastructure_memories m
  ON semantic_match(m.embedding, 'water pressure anomaly pipe burst', 0.7)
WHERE s.type = 'water_pressure'
ORDER BY risk DESC LIMIT 10;

72h

earlier issue detection

<50ms

trigger evaluation

40%

reduced emergency responses

Related Use Cases

Manufacturing & Quality Control

Agents correlate sensor data with historical defect patterns. Semantic triggers catch quality drift before defects ship.

View use case

Supply Chain Intelligence

Multi-agent crews monitor suppliers, routes, and inventory. Semantic triggers fire when anomalies match historical disruption patterns.

View use case

DevOps & Incident Response

Build institutional knowledge from past incidents. Semantic search surfaces relevant runbooks and resolutions instantly.

View use case

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