Demo data. Every figure, trend and prediction here is illustrative or generated, including what Chief of Staff quotes from it.

Data trust and AI

Watch

Can the numbers and models be trusted? · All concessions

Data quality score, last 12 monthsDemo: generated history, not measured data

All concessionsTarget

96939087

NovDecJanFebMarAprMayJunJulAugSepOct

Data quality score by concession

Worst first · line marks target · select to focus

Runs across all themes. Every headline KPI shows the share calculated from validated data, so you can see how far to trust each number.

RFP coverageGOB-01 · GOB-03 · IMP-01 · SEC-06 · AI-01

Supporting indicators

3 on target · 4 watch · 1 off target

Supporting indicators for All concessions: value, target, trend and status
Indicator	Value	Target	Status
Anomalies per 1,000 records, all sources	3.4	≤ 3.0	Watch
Open conflicts between sources	37	≤ 25	Watch
Time to resolve an anomaly, median	2.8 days	≤ 3.0 days	On target
False positive rate, anomaly checks	12%	≤ 10%	Watch
Feeds within freshness window	96.5%	≥ 98.0%	Watch
Geomic migration readiness (Group A)	73%	≥ 90%	Off target
Forecast accuracy	87%	≥ 85%	On target
AI recommendations accepted by operators	64%	≥ 60%	On target

Data quality by source

Data quality, anomalies and last refresh by source system
Source	Quality	Anomalies / 1,000	Last refresh
Surveys	93	3.1	6 h
Inspections	91	4.6	2 h
Traffic counts	97	1.8	5 min
Operational logs (TMC, SOS, SCADA)	95	2.4	1 min
Costs (ERP)	86	5.2	26 h, late

Geomic migration readiness

Transmontana82%

A23 Beira Interior76%

ACEGA / AP-5364%

Pocahontas Parkway71%

Ruta 2748%

M5088%

Line marks 90%, needed before cutover. Group B concessions are greenfield.

Along the route · Data coverageDemo: generated sections and forecasts, not measured data

Every network split into sections. Equal width; length in the label.

0 off · 0 watch · 11 on target
0 off · 5 watch · 7 on target
2 off · 2 watch · 1 on target
0 off · 0 watch · 3 on target
5 off · 0 watch · 1 on target
0 off · 2 watch · 2 on target
5 off · 1 watch · 1 on target
2 off · 1 watch · 0 on target
0 off · 0 watch · 3 on target

On targetWatchOff target (hatched)

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Supporting indicators for ACEGA / AP-53: value, target, trend and status
Indicator	Value	Target	Status
Anomalies per 1,000 records, all sources	3.7	≤ 3.0	Watch
Open conflicts between sources	4	≤ 2	Off target
Time to resolve an anomaly, median	3.1 days	≤ 3.0 days	Watch
False positive rate, anomaly checks	13%	≤ 10%	Watch
Feeds within freshness window	95.8%	≥ 98.0%	Watch
Geomic migration readiness (Group A)	64%	≥ 90%	Off target
Forecast accuracy	84%	≥ 85%	Watch
AI recommendations accepted by operators	56%	≥ 60%	Watch

Indicator

Value

Target

TrendDemo

Status

Anomalies per 1,000 records, all sources

3.7

≤ 3.0

Watch

Open conflicts between sources

≤ 2

Off target

Time to resolve an anomaly, median

3.1 days

≤ 3.0 days

Watch

False positive rate, anomaly checks

13%

≤ 10%

Watch

Feeds within freshness window

95.8%

≥ 98.0%

Watch

Geomic migration readiness (Group A)

64%

≥ 90%

Off target

Forecast accuracy

84%

≥ 85%

Watch

AI recommendations accepted by operators

56%

≥ 60%

Watch

Data quality, anomalies and last refresh by source system
Source	Quality	Anomalies / 1,000	Last refresh
Surveys	92	3.4	6 h
Inspections	89	5.0	2 h
Traffic counts	96	2.0	5 min
Operational logs (TMC, SOS, SCADA)	94	2.6	1 min
Costs (ERP)	83	5.7	26 h, late

Source

Quality

Anomalies / 1,000

Last refresh

Surveys

3.4

6 h

Inspections

5.0

2 h

Traffic counts

2.0

5 min

Operational logs (TMC, SOS, SCADA)

2.6

1 min

Costs (ERP)

5.7

26 h, late

Indicator

Value

Target

TrendDemo

Status

Anomalies per 1,000 records, all sources

3.4

≤ 3.0

Watch

Open conflicts between sources

≤ 25

Watch

Time to resolve an anomaly, median

2.8 days

≤ 3.0 days

On target

False positive rate, anomaly checks

12%

≤ 10%

Watch

Feeds within freshness window

96.5%

≥ 98.0%

Watch

Geomic migration readiness (Group A)

73%

≥ 90%

Off target

Forecast accuracy

87%

≥ 85%

On target

AI recommendations accepted by operators

64%

≥ 60%

On target

Source

Quality

Anomalies / 1,000

Last refresh

Surveys

3.1

6 h

Inspections

4.6

2 h

Traffic counts

1.8

5 min

Operational logs (TMC, SOS, SCADA)

2.4

1 min

Costs (ERP)

5.2

26 h, late

Supporting indicators for ACEGA / AP-53: value, target, trend and status
Indicator	Value	Target	Status
Anomalies per 1,000 records, all sources	3.7	≤ 3.0	Watch
Open conflicts between sources	4	≤ 2	Off target
Time to resolve an anomaly, median	3.1 days	≤ 3.0 days	Watch
False positive rate, anomaly checks	13%	≤ 10%	Watch
Feeds within freshness window	95.8%	≥ 98.0%	Watch
Geomic migration readiness (Group A)	64%	≥ 90%	Off target
Forecast accuracy	84%	≥ 85%	Watch
AI recommendations accepted by operators	56%	≥ 60%	Watch

Indicator

Value

Target

TrendDemo

Status

Anomalies per 1,000 records, all sources

3.7

≤ 3.0

Watch

Open conflicts between sources

≤ 2

Off target

Time to resolve an anomaly, median

3.1 days

≤ 3.0 days

Watch

False positive rate, anomaly checks

13%

≤ 10%

Watch

Feeds within freshness window

95.8%

≥ 98.0%

Watch

Geomic migration readiness (Group A)

64%

≥ 90%

Off target

Forecast accuracy

84%

≥ 85%

Watch

AI recommendations accepted by operators

56%

≥ 60%

Watch

Data quality, anomalies and last refresh by source system
Source	Quality	Anomalies / 1,000	Last refresh
Surveys	92	3.4	6 h
Inspections	89	5.0	2 h
Traffic counts	96	2.0	5 min
Operational logs (TMC, SOS, SCADA)	94	2.6	1 min
Costs (ERP)	83	5.7	26 h, late

Source

Quality

Anomalies / 1,000

Last refresh

Surveys

3.4

6 h

Inspections

5.0

2 h

Traffic counts

2.0

5 min

Operational logs (TMC, SOS, SCADA)

2.6

1 min

Costs (ERP)

5.7

26 h, late

Data trust and AI

Data quality score, last 12 monthsDemo: generated history, not measured data

Data quality score by concession

Supporting indicators

Data quality by source

Geomic migration readiness

Along the route · Data coverageDemo: generated sections and forecasts, not measured data

Add to OneTRL

Data trust and AI

Data quality score, last 12 monthsDemo: generated history, not measured data

Data quality score by concession

Supporting indicators

Data quality by source

Geomic migration readiness

Along the route · Data coverageDemo: generated sections and forecasts, not measured data

Section 3 of 5

Add to OneTRL

Data trust and AI

Data quality score, last 12 monthsDemo: generated history, not measured data

Data quality score by concession

Supporting indicators

Data quality by source

Geomic migration readiness

Along the route · Data coverageDemo: generated sections and forecasts, not measured data

Add to OneTRL

Data trust and AI

Data quality score, last 12 monthsDemo: generated history, not measured data

Data quality score by concession

Supporting indicators

Data quality by source

Geomic migration readiness

Along the route · Data coverageDemo: generated sections and forecasts, not measured data

Section 3 of 5

Add to OneTRL