I spent decades building thermal-imaging detection at SCD before founding GOTEAM. Those years taught me one thing:
A thermal core you can buy. You cannot buy an algorithm that reliably picks out a drone — a handful of warm pixels, moving, in a cluttered sky full of birds, clouds and heat noise — at the edge, in real time, month after month. That algorithm is years of field data, retraining and failure analysis. It is the heart of our system, and it never stops improving.
An improving algorithm and a growing fleet raise their own questions. By week three of any real deployment, these arrive:
- Is the unit on the northern site still healthy, or has it been quietly degrading for five days?
- A guard says "there was a drone last Tuesday night." Can you show it — or just believe it?
- Your algorithm improved this month. How does that reach thirty sensors on rooftops, vehicles and border masts without a technician and a ladder?
- Your customer's command-and-control wants the picture now, in a standard it already speaks.
Most counter-UAS marketing shows a detection and skips these questions. This week we published a page on the part of our stack that answers them: GOTEAM Hub, the management system behind every deployed GOTEAM sensor.
One live picture
Every node — fixed mast, vehicle, temporary deployment — reports in over whatever uplink exists: cellular, satellite, wired. The hub fuses them into one operational picture: nodes on a map with their true heading and field-of-view, and detections as threat-graded tracks with range, bearing, height and closing speed.
Every track carries a positional-uncertainty ellipse. A passive optical system knows its bearing well and its range less well, and the operator should see exactly that on the map, not a false-confidence dot.
Evidence, not anecdotes
Every detection is stored with its full-length annotated video, rendered automatically, plus zoomed thumbnails of the target and the complete track metadata — kept until you delete it. "What flew over the perimeter on Tuesday?" gets a video you can replay, export and attach to a report, not a logbook entry.
Because raw sensor frames are archived at the edge, a detection can be re-processed with a newer algorithm after the fact: last month's borderline event, examined again with this month's model.
The algorithm improves. The fleet keeps up.
The hub turns a retrained algorithm into fielded capability: one action rolls a new model to the entire fleet in about ten seconds. Each node pulls it, verifies its integrity and hot-swaps the live pipeline. No site visit, no downtime, nobody climbing a mast.
Sensors rarely fail loudly; they drift — a temperature creeping up, a camera delivering fewer frames each day. The hub keeps the health history of every unit and draws the trend, so a degrading node is a maintenance ticket this week instead of a coverage gap next month.
Plugged into command, not beside it
The hub speaks SAPIENT (BSI Flex 335 v2), as a server and as a client. Our detections stream to higher command in real time, and partner sensors plot on the same map. We built a detection layer, not a walled garden: your C2, your effectors, your decision.
Map, live feeds, alerts and replay also run on a phone: a native iOS app and an installable PWA.
Why I'm writing this
The counter-UAS market has an evidence problem and an operations problem, and both hide behind glossy detection demos until you own a fleet.
If you protect a site, a border or a principal, ask your C-UAS vendor how their algorithm got where it is, how it keeps improving in the field, and my four questions above. If the answers are vague, the protection will be too.
Ours are here: goteam.co.il/management.html
— Baruch
See the hub with your own nodes on it.
We'll walk you through a live deployment — real sensors, real detections, real C2 feed.