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Documentation Index

Fetch the complete documentation index at: https://docs.vangrid.io/llms.txt

Use this file to discover all available pages before exploring further.

Edge nodes are the physical foundation of the Vangrid network. Each node is a sensor-equipped device that continuously captures spatial observations from its environment, processes them locally, and contributes signed data to the network. With more than 3 billion nodes already deployed worldwide, you can query dense spatial coverage across urban environments without owning, installing, or operating any hardware yourself.

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The zero-capex sensor swarm model

Traditional spatial data workflows require you to procure sensors, manage deployments, handle maintenance, and build ingestion pipelines. Vangrid eliminates all of that. The network is already deployed — you access it through the API. 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 query volume and data egress, not for sensor uptime or coverage. Node infrastructure costs are absorbed by the Vangrid network — not passed through to your account.
This model is sometimes called a “zero-capex sensor swarm” because you gain access to a massive, continuously operating sensor deployment with no capital expenditure. You pay only 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 centers, coverage is sparser. Vangrid’s API returns a node_count field in every response indicating how many nodes contributed to a given observation. Lower node counts warrant scrutiny of the accompanying ground_truth_score.

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Multi-view ingestion

Nodes across the network use heterogeneous sensors — different sensor types, orientations, elevations, and modalities. When you query an AOI, the observations returned may come from cameras, depth sensors, lidar, or other modalities depending on what nodes are deployed in that area. 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.
  • Cross-modal corroboration — Agreement between, for example, a camera-based observation and a depth-sensor observation increases confidence in the result.
  • Redundancy — If a node goes offline or produces a low-quality observation, other nodes covering the same area 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.