Stage 01
Sense
CityFix collects infrastructure signals from systems already moving through the city.
CITYFIX — AI infrastructure intelligence
Cities shouldn’t have to wait to know what’s broken.
CityFix turns cameras, fleets and citizen reports into real-time infrastructure intelligence.
01 — The problem
Urban maintenance is still reactive.
- Discovered late.After damage has already grown
- Reported manually.By residents, across many channels
- Routed slowly.Inbox → department → team
- Fixed reactively.When complaints pile up
More reports don’t necessarily mean better infrastructure intelligence.
Make infrastructure self-reporting.
The CityFix vision — infrastructure that tells you when it needs attention
02 — System
From street
to action.
One intelligence layer connecting detection, decisions and maintenance.
Stage 02
Understand
Computer vision structures the physical world into usable infrastructure data.
Stage 03
Prioritise
Severity, location, asset, traffic, recurrence and impact combine into a score — and a person signs it off.
Stage 04
Act
Turn intelligence into an actionable workflow — not another dashboard.
Stage 05
Verify
Each repair is checked against a fresh observation, and the result flows back into the system.
What a person seesWhat CityFix sees
Drag to compare
03 — CityFix Vision
Every vehicle can become an inspector.
Municipal fleets already drive the city’s streets every day. A camera on board turns each route into a continuous, low-cost inspection pass.
We don’t need more roadside inspections.
We need to make every drive count.
Illustrative simulation — detections and confidences are examples, not measured performance.
CITYFIX / CommandSector view · Sample cityIllustrative interface · sample data
The CityFix command interface
Active issues
128sample
Road health index
72/ 100
Work orders
- WO-1182Sector 2 RoadAssigned
- WO-1179Waste Ops NIn progress
- WO-1174Signage BVerified
Issue types
Area
- Sector 181
- Sector 268
- Sector 374
- Sector 477
Last detected
- 08:42 Pothole · Seg 0482
- 08:39 Crack network · Seg 0471
- 08:31 Waste overflow · Bin 2203
CF-20841 Active
Road surface damage
Confidence 94% · Detected 08:42 · Priority 82
WO-1182 Assigned
Sector 2 Road Team
Route calculated · ETA 18 min · Crew en route
CF-20841 Resolved · pending verify
Repair logged
Next fleet pass re-checks the segment
Illustrative interface — sample data, not a live deployment.
From reactive to predictive
Seeing what’s broken is only the beginning.
Today
Detect
Find issues automatically from photos and fleet footage.
Current prototype
Next
Understand
Attach each issue to an asset, a location and its history.
Pilot target
Then
Anticipate
Spot segments that are degrading faster than expected.
Long-term vision
Eventually
Predict
Estimate what will fail next, and which fix will last.
Long-term vision
T0 · Healthy
Jan · condition 92
T1 · Surface wear
Mar · condition 83
T2 · Crack
May · condition 64
T3 · Pothole
Jul · condition 36
T4 · Repair
Aug · condition 90
T5 · Recurrence
Nov · condition 58
Illustrative timeline · condition index is an example
Long-term platform vision
City condition graph
The long-term advantage isn’t knowing that a pothole exists. It’s understanding what breaks, where, how quickly, what fixes it — and whether that fix lasts.
The city condition graph
Every repair becomes memory.
Each observation, intervention and recurrence links assets by location, history, contractor, repair, cost and outcome — a record of how a city’s infrastructure actually behaves.
CityFix does not hold this dataset today. It is what continuous operation would build.
04 — Impact
Fix earlier. Waste less.
Environmental impact and financial return point the same way: catch damage while it is small, drive fewer unnecessary kilometres, survey less by hand, and spend maintenance budgets where condition says they matter.
01
Earlier maintenance
→ Longer asset life→ Less reconstruction
02
Smarter routes
→ Fewer unnecessary→ fleet kilometres
03
Targeted inspection
→ Less manual→ surveying
04
Better asset data
→ Better maintenance→ allocation
Measurement frameworkNo CityFix impact figures exist yet — these are set in a pilot
Km of inspection avoidedMeasured during pilot
Fleet km reducedMeasured during pilot
Preventive interventionsMeasured during pilot
CO₂e avoidedCalculated from verified pilot data
05 — Scale
One intelligence layer. Many physical systems.
Expansion vision — not current customers
Asset classes · roads first
Operators
- Roads
- Waste
- Signage
- Sidewalks
- Drainage
- Vegetation
- Public realm
- Cities
- Airports
- Ports
- Campuses
- Logistics parks
- Road operators
- Industrial sites
Business model
Start narrow. Expand with the infrastructure.
- CityFix Core: Annual platform licence
- CityFix Vision: Vehicle, camera & processing usage
- CityFix Modules: Roads · Waste · Analytics · Integrations · Predictive intelligence
- 011 pilot
- 021 fleet
- 031 asset class
- 04Multiple modules
- 05Multiple operations
- 06Multiple cities / operators
Pricing and unit economics remain subject to pilot validation.
Roadmap — the long-term vision
The operating system for physical infrastructure.
Whether the work is performed by a municipal crew, contractor or autonomous machine, CityFix becomes the intelligence layer coordinating what needs to happen.
CityFix does not manufacture robots or vehicles. It orchestrates the work.
01
Detect
Find what's broken without waiting for a report.
Current prototype02
Coordinate
Turn every finding into owned, routed, verified work.
Pilot target03
Predict
Learn what fails, where and how fast — and act first.
Long-term vision04
Automate
Dispatch to whoever, or whatever, can do the job.
Long-term vision
Start with one road. One fleet. One pilot.
CityFix is looking for municipalities and infrastructure operators willing to test continuous AI-assisted infrastructure monitoring.