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An edge node is a person’s phone running the Vangrid capture app. That is the whole of it. There is no hardware to ship, no fleet to maintain, and no installation. A contributor opens the app, records a capture of a place, and the device signs and submits it. The network is built to run on the phones people already carry, which is the only sensor deployment that reaches street level everywhere at once. Coverage therefore follows people rather than infrastructure. It is densest where contributors are active and thin where they are not, and it grows through bounties: a request for a specific place, funded, that contributors compete to fulfil.

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No hardware to deploy

Traditional spatial data workflows require you to procure sensors, manage deployments, handle maintenance, and build ingestion pipelines. Vangrid removes that layer. You access captured data through the API, and commission new captures through bounties. When you make a spatial query, Vangrid identifies which nodes cover your area of interest, routes your request to them, aggregates their responses, and returns a single verified payload. From your perspective, the network behaves like a continuously operating sensor grid that you query on demand.
You are billed for the data you retrieve and for the bounties you fund. There is no hardware cost to pass on.
There is no capital expenditure on sensors, because the sensors are phones that already exist. You pay for the data you retrieve.

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Node density and coverage

Vangrid’s network is designed for tactical urban density, the highest node concentrations are in metropolitan areas where autonomous systems, logistics, and infrastructure monitoring have the greatest need for fine-grained, continuous spatial data. In dense urban environments, multiple nodes typically cover any given location simultaneously, often from different vantage points and elevations. This overlap is intentional: it enables multi-view corroboration, which is the mechanism Vangrid uses to calculate the ground_truth_score for each observation.
Coverage density varies by region. Contact hello@vangrid.io to confirm node coverage for a specific AOI before building production workflows that depend on it.
Outside major urban centres, coverage is sparser. Where a place is not covered, post a bounty for it.

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Multi-view ingestion

Captures of the same place come from different people, at different times, from different positions and heights. When you query an area of interest, the observations returned are drawn from those independent captures. Multi-view ingestion means the Vangrid aggregation layer combines observations from nodes with different physical perspectives and sensor types. This produces several advantages:
  • Occlusion handling, An object hidden from one node’s line of sight is often visible to another.
  • Independent corroboration, Agreement between captures recorded by different contributors at different times increases confidence in the result.
  • Redundancy, If one capture is low quality, other captures of the same place continue contributing.
The sensor_modalities array in each API response lists the sensor types that contributed to that observation, so you can filter or weight results based on the modalities your application depends on.

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How nodes are selected for your query

When you submit a spatial query, you specify an area of interest (AOI) as a GeoJSON polygon or bounding box along with a time range. Vangrid’s routing layer identifies all active nodes whose coverage intersects the AOI during the requested time window. Node selection factors include:
  • Geographic overlap, The node’s coverage area must intersect your AOI.
  • Temporal availability, The node must have been active and capturing during your requested time range.
  • Data quality, Nodes with persistent quality issues or flagged hardware are deprioritized.
  • Sovereignty boundary, Only nodes within your configured data boundary are eligible.
Smaller AOIs return faster responses with higher node density per unit area. If you need broad coverage, consider issuing multiple targeted queries rather than a single large-polygon query.

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Edge-computed privacy

Every node processes raw sensor data locally before transmitting anything to the network. Raw frames, point clouds, and sensor streams never leave the device. What the node transmits is a structured feature payload, spatial geometry, object classifications, timestamps, and metadata, derived from the raw data but containing no recoverable raw content. This means:
  • Personally identifiable information (faces, license plates, biometrics) is never present in API responses.
  • Sensitive scene details are not stored or transmitted by the infrastructure.
  • Privacy compliance is enforced at the hardware boundary, not in a downstream filtering layer that could be misconfigured or bypassed.
Edge-computed privacy is a network-level guarantee, not a configurable option. It applies to all nodes in the Vangrid network regardless of deployment region or query type.
Last modified on August 8, 2026