Software that Doesn't
Blink

You already have eyes on the campus.
TitanOps makes sure nothing gets past them.

20 Minutes

That’s roughly how long a trained, motivated person can stare at a wall of monitors before their brain starts filling in gaps instead of catching them. This is not a discipline problem nor a training problem, it’s documented human biology that’s held true since the 1940s.¹

Detection accuracy: 85% on one screen → 53% on nine.²

Vigilance decrement: measurable degradation within 20–30 minutes of continuous monitoring;¹ “video blindness” reported after 20–40.³

Live detection rate: only ~35% of real detections are caught live, the rest are found after the fact.⁴

The Solution

TitanOps doesn’t ask your team to concentrate harder. It removes the need to.

TitanOps is an AI layer that watches a campus’s existing camera feeds continuously and surfaces only what requires a human decision. Alerts stay relevant through zone/shift filtering, carry operator notes for clean handoffs, and route to text/email or existing external systems.

TitanOps also generates shift summaries so teams leave behind a documented record rather than relying solely on memory.

The Questions Worth Asking

What’s happening on your cameras at 3 AM? A side door. An empty quad. A tile nobody’s watching right now. TitanOps is, it flags the moment and texts your on-duty officer directly.

How would you know if one entrance started filling up faster than the rest? Real-time people-counting tracks crowd levels by zone, and a density spike routes straight to whoever’s covering that area, before it becomes a problem, not after.

What does your shift handoff actually look like right now? A verbal recap? A notebook? Memory? TitanOps auto-generates a documented summary, so the next shift starts with a clean record instead of a rushed one.

If you added a drone next year, how would your team need incorporate it? With TitanOps they just extend what they already have. Mission planning, full control, payload ingestion and analysis, and replay-and-reanalyze on any past flight all live in the same pane of glass from day one.

Ask Your Current Setup

Does an alert actually reach someone, or does it just sit in a feed nobody’s watching? (Ours routes to text, email, or your existing systems.)
Do you know how many people are in a space right now, or are you guessing? (Ours counts, live, on the map.)
Are your alerts organized by zone and shift, or is everyone drowning in the same feed? (Ours filters down to what’s relevant.)
Is there a real record of last night’s shift, or just what someone remembers? (Ours generates one automatically.)
What happens when you add a camera, sensor, or drone. Does it force you in to a new vendor, or one more login on what you already have? (Ours: one API, same dashboard.)
Does your flight software talk to your security dashboard at all? (Ours is the same pane of glass — full mission planning, manual control, and replay-and-reanalyze on any past flight.)

Curious what your existing cameras could actually catch?

¹ 1940s radar-operator vigilance decrement research (Mackworth; replicated across applied cognitive psychology literature since).

² Operator detection-accuracy vs. screen-count study (1, 4, 6, 9-screen comparison).

³ Velastin et al. (2006), CCTV ‘video blindness’ after 20–40 minutes of continuous monitoring.