VIDIZMO integration brief · Flock Safety (FlockOS) · vidizmo.ai/integrations/catalog/flock-safety-flockos

Integrations / Flock Safety (FlockOS)

Flock Safety (FlockOS)

Bring FlockOS detections and camera video into the evidence record. Visit website

FlockOS is Flock Safety's real-time crime centre platform, unifying licence plate recognition, cameras, drones, audio detection and CAD feeds on one live map.

Detections and the footage behind them are ingested so a plate hit or an alert becomes evidence with retention and an audit trail, rather than a notification that expires. The camera estate is also reachable as a live source for analysis.

A Plate Hit That Becomes Evidence Instead of a Notification

Open as a two-page brief

This connector is not prebuilt. It would be built to your requirement on the REST API, the ingestion path and the RTSP path the platform already uses, with scope and effort agreed per engagement. FlockOS is Flock Safety's real-time crime centre platform, bringing licence plate recognition, cameras, drones, audio detection and dispatch feeds onto one live map. It is built for the moment something is happening. The gap it leaves is what happens afterwards, when a notification has expired and someone needs the record.

How it connects

Two distinct paths, and they answer different questions. Detections and the footage behind them would be ingested over the Flock API, so a plate read or an alert becomes an item in the library with retention, access control and a custody record rather than an entry in a feed that ages out. The detection's own data would arrive as attributes on that item, which is what lets it be found later by plate, time or location.

Separately, the camera estate would be reachable as a live source over RTSP, where a camera publishes a stream the platform can read. That is the path for running detection on those streams in AI Live Insight, and it is a different piece of work from ingesting what Flock has already detected. An engagement would establish which cameras publish a reachable stream before either is committed.

FlockOS would stay the real-time picture. The live map, its alerting and its own analysis stay with Flock, and the platform's role is the record and the analysis that happens after. Where both systems can raise an alert on the same event, an engagement would settle which is authoritative, because two alert streams reaching one operator is worse than one.

What you can do together

  • Keep a plate read and the footage behind it as evidence with retention and a custody record, so it is answerable to a request months later.
  • Find a detection by plate, time or location from the attributes it arrived with, rather than by scrolling a feed.
  • Run detection on Flock cameras as live sources through AI Live Insight, where a camera publishes a reachable stream.
  • Have a workflow assemble everything relating to one vehicle across detections, footage and case material, with a person reviewing before it goes anywhere.

A scenario

  1. ScopingThe engagement would agree which detections and footage are ingested, which cameras publish reachable streams, and which system owns which alert.
  2. SetupThe connection would be configured once against the Flock API, with detection data mapped to attributes on the ingested items.
  3. An incidentA plate read on a vehicle of interest ingests with its time, location and image, filed under the case folder with its custody record started.
  4. The investigationAn analyst asks for everything on that plate over a fortnight and gets the detections, the footage and the related case material in one answer, each cited.
  5. Months laterA disclosure request arrives and the record is intact, which is the thing a notification could never have provided.

What stays where

FlockOS remains the real-time picture

The live map, its own alerting and its analysis stay with Flock, and the centre works as it does now.

The platform holds the record and what comes after

Retention, access control, custody and later analysis apply to what was ingested.

The two paths are separate work

Ingesting detections is one piece; reading cameras as live sources over RTSP is another, and each is scoped on its own.

Processing runs where you deploy the platform

Live analysis on camera streams runs on a server on the camera network, which is what keeps it timely; the record itself can sit in any deployment.

Products and solutions

Next step

See it on your own Flock Safety (FlockOS) instance. We will show the connection made, the data moving and the output, then size it for your deployment.

Request a demonstration  or write to sales@vidizmo.ai

sales@vidizmo.ai  ·  vidizmo.ai/integrations/catalog/flock-safety-flockos

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