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Vangrid is a decentralized data rail, a continuously growing network of edge nodes that captures real-world spatial observations, filters them for privacy on the device that recorded them, and delivers verified results to your application through a single REST API. Understanding how data moves through this pipeline helps you write better queries, interpret responses correctly, and design systems that rely on ground truth rather than approximations.

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Key terminology

Before walking through the pipeline, it helps to understand the core terms you’ll encounter throughout these docs.
Ground truth refers to verified, real-world spatial observations captured directly by physical sensors. In Vangrid’s context, ground truth data is corroborated by multiple independent edge nodes and accompanied by a cryptographic provenance hash that proves its origin and integrity. Ground truth is distinct from inferred or synthetic data, it reflects what actually existed in the physical world at a specific place and time.
An edge node is a phone running the Vangrid capture app. Nodes capture multi-view video of a place, and faces and vehicle number plates are obscured on the device before the video is encoded. You never purchase or manage edge nodes: you query the network, and Vangrid routes your request to the nodes that cover your area.
A provenance hash is a cryptographic signature attached to every Vangrid data response. It encodes the identity of the originating node, the capture timestamp, and a hash of the raw observation, giving you tamper-evident proof that the data hasn’t been altered between capture and delivery. You can use the hash to audit, archive, or independently verify any response.
A spatial query is an API request that specifies a geographic area of interest (AOI), a time range, and optional filters. Vangrid routes the query to edge nodes that cover the AOI, aggregates their responses, and returns a ranked, provenance-stamped payload. Queries can return real-time observations or historical records.
The data rail is Vangrid’s end-to-end pipeline, from edge capture through edge-compute, cryptographic signing, aggregation, and API delivery. Calling it a “rail” emphasizes that data moves along a defined, governed path with sovereignty controls at each stage, rather than being routed through arbitrary third-party infrastructure.

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How data flows through Vangrid

The pipeline moves data from the physical world to your application in five stages.
1

Capture

Edge nodes capture spatial observations from their environment. Each node operates independently, and nodes in the same area observe the same scene from different positions and at different times, producing multi-view coverage that no single pass can. The ingestion path is sensor agnostic by design: as phones ship with depth and lidar sensors, those modalities will flow through it without a change to the query interface.
2

Edge compute

The node runs detection on every frame as it is recorded and obscures faces and vehicle number plates before the video is encoded. The unblurred frames never leave the device: they are not uploaded, not stored, and not recoverable later. Privacy is enforced at the moment of capture rather than by policy after the fact. Extracting spatial features on the node itself, so that only the derived payload is transmitted, will follow as device compute allows.
3

Cryptographic signing

After local processing, each node signs its observation with a private key. The resulting provenance hash encodes the node identity, capture timestamp, and observation content. Any downstream modification to the data would invalidate the signature, giving you a verifiable chain of custody from sensor to API response.
4

Aggregation

Signed observations from multiple nodes covering the same AOI are aggregated by Vangrid’s infrastructure. Observations are cross-corroborated to produce a ground_truth_score, a confidence metric that increases as more independent nodes agree on the same spatial state. Conflicting observations are flagged rather than silently discarded.
5

API delivery

The aggregated, scored, and signed payload is returned through the Enterprise Spatial API as structured JSON. Each feature in the response includes geometry, timestamps, ground_truth_score, and provenance_hash. You can use the response directly, stream it to downstream systems, or archive it with the provenance hash for future audits.
Vangrid routes every query through nodes within your designated data sovereignty boundary. Data does not transit infrastructure outside that boundary unless you explicitly configure cross-region access.

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What makes this different from cloud-first alternatives

Most spatial data platforms send whatever the sensor saw to a central cloud and filter it there, if at all. Two problems follow: identifiable footage exists in someone else’s infrastructure, and there is no per-observation provenance to audit. Vangrid inverts this model. Filtering happens on the device, so no version of a capture in which a face or a number plate is legible exists anywhere off that device. Provenance is attached at the source, and the API layer is a thin delivery surface over the network. You get stronger privacy guarantees and a verifiable record for every observation, without deploying any infrastructure.
If you are building a system that needs to demonstrate data integrity to regulators, auditors, or partners, store the provenance_hash from each response alongside your application data. You can use it to reconstruct and verify the chain of custody at any time.

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Explore the pipeline in depth

Edge nodes

How the node network is structured, how nodes are selected for your queries, and what multi-view ingestion means in practice.

Data pipeline

A step-by-step breakdown of how data moves from capture through signing to your API response, including latency and format details.

Ground truth

How Vangrid defines and calculates ground truth, what the ground_truth_score means, and when to use real-time vs. historical data.
Last modified on August 11, 2026