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Use cases

The rest of this documentation is organized by surface: here is the query editor, here is the feed page, here is what each field does. These guides are organized by goal instead. Each one takes a single goal an agency has and walks it from the data you already hold to something a reader outside your team can use.

There are eighteen guides here, in five groups. Nearly all of them are written to the same five parts, in the same order:

PartWhat it holds
What has to be trueThe requirement, stated as the consumer or the regulator states it, not as the product states it
Before you startWhat must already exist. Usually a query that has run at least once, and a credential
The stepsThe path, in order, naming the page each one happens on
How you know it workedThe check that settles it, run from outside the instance wherever one exists
What takes it off the airThe failure modes, written down before you run into one

The short ones collapse that to steps and honest limits, leaving out the middle sections where they would have nothing to say.

The guides come in two kinds. Some drive a product feature end to end, and every step is a page in this documentation. Others are recipes over data that is yours, where the product handles the ingest, the schedule, the query and the board, and the credibility of the numbers rests on your own systems. Each guide says which kind it is, and what it will not do for you.

Unless a step says otherwise, everything described is in the community edition. Steps that need the enterprise edition say so where they appear, and where a capability is split down the middle the guide states which half falls where: reading a private feed is community, issuing the token it is read with is enterprise; ingesting trip updates and service alerts is community, publishing them is enterprise.

Publishing a feed

GuideWhat you end up with
Publish a GTFS-Realtime feedVehicle positions at a public address, in protobuf, validated before every publish
Publish a GBFS feedA whole GBFS system, docked or free-floating, at an address a city permit or an aggregator can be pointed at
Query a static GTFS archiveThe schedule tables behind both of those, queryable beside the realtime feeds and checkable before anything depends on them
Take a feed back from a vendorThe same feed served from your own node, proven equivalent before anyone is asked to move

Reporting and evidence

GuideWhat you end up with
Assemble a monthly ridership packUPT, VRM, VRH and VOMS by mode and type of service, from the systems of record, reconciled against a month you have already filed
Derive NTD service data from your GTFS archiveRoute, trip and service-day counts read off the schedule you already publish, with the archive checked first
Report on demand-response serviceDenials, missed trips, untimely pickups and ride length out of the dispatch system, on definitions written down once
Build a service equity boardStops and service assigned to your own tract or district boundaries, shaded on a map, on attributes you bring
Prove your captures are currentA declared cadence on every capture, so freshness is a verdict the product reaches rather than a claim the data makes about itself

Operating pictures

GuideWhat you end up with
Put a traffic management center on your boardActive events and sign status from a TMDD center, on dashboards of your own
Read a DMS fleet over NTCIP 1203Every sign's identity, status and current message, with unreachable signs visible as rows rather than as a failed query
Build an incident and air quality pictureTraffic alerts, air quality and weather on one auto-refreshing grid, with a reliability floor that keeps the noise out

Analysis over time

GuideWhat you end up with
Build a history you can trendQuery results accumulating into a warehouse table, which is what every recipe below is built on
On-time performanceOTP% by route and day, computed from the delays your own trip-update feed reports
Track fleet utilization from telematicsVehicles in service by hour, and the list of vehicles that have not moved in a week

Getting data back out

GuideWhat you end up with
Ask your data from an AI clientClaude Desktop or an IDE reading your instance over MCP, read-only, scoped to your own permissions
Publish an open-data pageA dashboard the public reads without an account, and an embed that survives being pasted into another site
Distribute a feed to a named partnerOne consumer reading a private feed on a credential you issued them and can revoke on its own

What these guides do not do

They do not author your schedules, your fares or your service, and they do not count passengers. Veodyn moves, normalizes, stores, draws and republishes data that some other system is the source of. Where a guide's real answer is "fix it upstream", it says so rather than routing you through a workaround that hides the defect one layer down.