Grid Intelligence
Identify and estimate distributed energy assets such as rooftop solar and combine them with weather and network context.
Read more →Energy Infrastructure Intelligence
Vink Energy
See infrastructure more clearly. Plan the grid faster.
Vink Energy combines geospatial data, imagery, network information and AI to improve visibility, forecasting and planning for energy infrastructure.
Core problems
What gets in the way of grid decisions
- 01
Make invisible or fragmented infrastructure more observable.
Distributed assets and local generation are not always visible in one consistent dataset.
- 02
Improve estimates where current records are incomplete.
Combine imagery, spatial and network data to fill gaps, and state how uncertain each estimate is.
- 03
Prepare reinforcement work using more complete spatial context.
See routes, constraints and obstacles before crews are sent into the field.
Use cases
Two initial use cases
Grid Build Intelligence
Combine spatial, infrastructure and field information to identify routes, constraints, obstacles, risks and differences between plans and physical reality.
Read more →Data
Data layers
Each engagement combines the layers that are relevant and available.
- Earth observation
- Aerial imagery
- BAG and public spatial information
- Weather
- Network information
- Field observations
- Customer data
We do not assume access to proprietary network data. Network and customer data are used only where the customer provides them, under agreed terms.
Pilot
How a bounded pilot works
A pilot tests whether better spatial intelligence changes a decision, measured against how the work is done today.
- 01
Existing process
Agree the decision, the area and the current way of working as the baseline.
- 02
Vink-assisted process
Run the models on the agreed data for the same area and period.
- 03
Compare results
Measure both against the baseline and against what actually happened.
- 04
Decide
Decide whether deployment creates value, needs refinement, or should stop.