Overview
An intelligence platform that unifies your data and knowledge into an operational ontology.
The Aerovy Platform is an intelligence platform. It unifies the data and knowledge scattered across your organization into a single operational ontology — a structured, living model of your domain — and enables authoring workflows composed from that ontology's primitives. The result: the institutional knowledge that used to live in people's heads and static documents becomes durable, executable tasks that run on their own.
What it unifies
The platform brings four kinds of input into one model:
| Input | What it is |
|---|---|
| Hardware data | Telemetry from connected devices: batteries, swap stations, chargers, meters, and vehicles. |
| Third-party data | Data pulled in from external systems through Integrations — Geotab, Zubie, UtilityAPI, and others. |
| Unstructured data | Documents, specifications, and fileshares that describe how your domain actually works. |
| Institutional knowledge | The rules, expertise, and judgment your teams carry — the know-how behind day-to-day decisions. |
Everything is scoped to your organization.
The operational ontology
These inputs are unified into an ontology: a single structured model that names and relates the entities in your domain. It's built from a few reusable primitives:
- Thing Type Definitions describe the kinds of entities you operate — a battery, a charger, a product model.
- Metric Definitions describe the quantities they measure or derive — state of charge, tolerances, mean time between failures.
- Templates map external and unstructured payloads onto those definitions so new data lands in the model consistently.
- Integrations connect external systems to ingress data in and egress data and notifications out.
- Transactions capture templatable records of business and operational events.
- Monitors provide configurable, real-time observability over your metrics.
- Agents are out-of-the-box models that execute specialized tasks — forecasting, anomaly detection, and more.
The ontology is operational, not a static graph with executable primitives that represent distinct units of work. The Ontology Agent builds durable context from your documents and data sources and keeps it current as those sources change. See Data model for how the primitives fit together.
Workflows: knowledge as executable tasks
Once your domain is modeled, you author workflows composed from ontology primitives: a trigger plus a sequence of steps that query data, run agents, command hardware, or call integrations. Each workflow encodes a real company task — alert response, a hardware action, an integration handoff, scheduled planning — as a durable, executable version of it.
This is how institutional knowledge stops decaying: instead of living in a runbook or a single expert, the decision logic is captured in a workflow that runs the same way every time, captures performance data on each run, and improves as feedback arrives.
The API
You interact with the platform through a single REST API, the Aerovy Platform API: one HTTPS + JSON service for everything you do.
- Write. Register Things, Sites, Fleets, and Integrations; define your Thing Types and Metrics; and send telemetry.
- Read. Query a Thing's metric history, aggregate over time windows, and fetch latest snapshots.
The API is versioned in the URL path (/v2/…), and its base URL is environment-specific (for
example https://spectra.dev.aerovy.com in dev). See
API fundamentals for base URLs,
authentication, versioning, and errors.
How data gets in
You don't always have to send data yourself:
- Direct ingestion: you call the telemetry endpoint with your own readings. This is the path covered in Ingesting data.
- Integrations: the platform pulls or receives data from a third-party system on your behalf (Geotab, Zubie, UtilityAPI, and others). You configure an Integration once, and the platform maps the external devices onto your Things automatically.
Once data is flowing, Querying data covers reading it back out.