Curitiba
Metro Power
31.8
of 100 · #129
MPI
31.8
MCC
28.2
MDI
26.2
Pillar profile
Talent29.3
Capital16.9
Research23.2
Infrastructure45.4
Agentic26.2
Indicators
- Population (m)3.7
- GDP ($bn)65
- GDP per capita ($k)17.6
- AI investment ($bn)0.3
- Tech employment %4.8
- AI talent45
- Research strength48
- Notable AI orgs9
- Compute / data centers50
- Broadband %80
- Tertiary degree %34
- Digital skills51
- Startup ecosystem48
- Agent adoption31
- Patents / 100k8
Nearest peers
- Bogota28.8
- Medellin29.0
- Johannesburg29.3
- Ho Chi Minh City29.4
- Cape Town29.4
Metro report · generated from Curitiba's indicators
Curitiba, metro standing in full
Curitiba is the #126 metro by economic size ($65bn) in the panel and ranks #129/162 on absolute Metro Power and #144/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is capital. Locally it runs below the Brazil national average (MCC 28.2 vs CC 41.1).
National context: Brazil scores CC 41.1 per-capita; Curitiba sits at MCC 28.2.
Economic & scale context curated v1 estimate
GDP (metro)
$65bn
#126 of 162
GDP / capita
$18k
Population
3.7M
AI investment
$0.3bn
#148 of 162
Notable AI orgs
9
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Curitiba's own standing.
| Index / pillar | Value | Standing | What a high vs low value means, and where Curitiba sits |
|---|---|---|---|
| MPI Metro Power | 31.8 | Developing · #129/162 | Low here, limited absolute weight, a smaller node that leans on capacity built in larger hubs. ▲ high: a heavyweight hub where capital, talent and AI organizations concentrate, it can anchor an entire national AI ecosystem · ▼ low: limited absolute weight, a smaller node that leans on capacity built in larger hubs |
| MCC Metro Coefficient | 28.2 | Lagging · #144/162 | Low here, thin intensity per resident, capability is sparse relative to the population. ▲ high: deep capability per resident, a concentrated, high-intensity ecosystem · ▼ low: thin intensity per resident, capability is sparse relative to the population |
| MDI Metro Agentic | 26.2 | Lagging · #143/162 | Low here, agentic deployment is shallow, the local agent lever is under-used. ▲ high: agents are widely deployed locally, a near-term productivity multiplier · ▼ low: agentic deployment is shallow, the local agent lever is under-used |
| Talent Talent | 29.3 | Developing · #136/162 | Low here, a shallow talent base that constrains how much can be built locally. ▲ high: a deep talent pool, the scarcest input to building AI · ▼ low: a shallow talent base that constrains how much can be built locally |
| Capital Capital | 16.9 | Lagging · #146/162 | Low here, thin investment, good ideas struggle to scale locally. ▲ high: abundant capital flowing into building cognitive infrastructure · ▼ low: thin investment, good ideas struggle to scale locally |
| Research Research | 23.2 | Developing · #141/162 | Low here, a weak research base, fewer home-grown breakthroughs and spinouts. ▲ high: a strong research base feeding a pipeline of ideas and people · ▼ low: a weak research base, fewer home-grown breakthroughs and spinouts |
| Infrastructure Infrastructure | 45.4 | Developing · #136/162 | Low here, infrastructure gaps cap how much AI can actually be run locally. ▲ high: the physical and digital rails to run AI at scale are in place · ▼ low: infrastructure gaps cap how much AI can actually be run locally |
| Agentic Agentic | 26.2 | Lagging · #143/162 | Low here, little agentic deployment, the near-term lever is unused. ▲ high: agents are actively deployed, an early-mover productivity edge · ▼ low: little agentic deployment, the near-term lever is unused |
Strengths to build on
- No pillar stands out as a clear strength yet.
Risk factors
- Binding weakness, Capital 16.9 (#146/162, Lagging): thin investment, good ideas struggle to scale locally.
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Metro values are curated estimates (v1) on a consistent global scale, not yet measured sub-national data.