Most security cameras are excellent historians.
Something happens. A fire starts. Someone breaks in. Property gets damaged. Then everyone gathers around a screen afterward and watches exactly how the disaster happened.
Useful?
Sure.
Ideal?
Not really.
In this episode of Legacy Launchers, I sat down with Xavier Espinosa, Co-Founder of Monitour AI, to talk about a much more interesting question:
What if security cameras could recognize danger while it was happening—and help people respond before the situation became a catastrophe?
That is the problem Xavier and his team are working on.
From Recording Problems to Recognizing Them
Traditional security-camera systems are primarily reactive.
They record.
They store footage.
They provide evidence.
But someone usually still has to notice that something is wrong.
AI changes that equation.
Instead of treating a camera as a passive recording device, computer vision can potentially turn it into something closer to an intelligent monitoring system—identifying patterns and events that deserve immediate attention.
That could include situations involving:
- Fire
- Burglaries
- Vandalism
- Suspicious activity
- Potentially dangerous behavior around a property
The shift sounds subtle, but it changes the entire purpose of surveillance.
The old question was:
“What happened?”
The new question becomes:
“What is happening right now, and can we do something about it?”
The $200,000 Problem
One of the stories that stood out during our conversation involved a potentially devastating fire and roughly $200,000 in potential damage.
That example gets to the heart of the business case for AI-powered physical security.
A security camera recording a fire is useful for understanding what happened afterward.
A system that can recognize the potential fire quickly enough for someone to intervene is much more valuable.
Seconds matter.
Especially in commercial real estate, warehouses, offices, multifamily properties, construction sites, and other environments where one small incident can become an extremely expensive one.
The same principle applies to vandalism or intrusion.
Knowing who broke into your property yesterday has value.
Knowing someone may be breaking into it right now has considerably more.
AI Is Moving Into the Physical World
A lot of the current AI conversation revolves around ChatGPT, writing, marketing, coding, and office productivity.
Those applications are important.
But AI’s impact is going to extend far beyond things happening on a laptop.
Companies like Monitour AI represent another side of the AI revolution:
AI interacting with the physical world.
Cameras already generate enormous amounts of visual information.
The challenge is that humans cannot realistically watch every camera every second.
AI can potentially act as an additional layer of attention.
Instead of asking a property manager, security employee, or business owner to stare at dozens of feeds all day, software can analyze what the cameras are seeing and surface situations that may require human intervention.
That’s a much more compelling use of automation.
AI doesn’t necessarily replace the person making the decision.
It helps the person notice the thing that needs a decision.
Your Existing Cameras Could Become Smarter
One of the most interesting opportunities in this space is that businesses already have cameras everywhere.
Drive through almost any commercial area and you’ll see them.
Office buildings.
Parking lots.
Restaurants.
Warehouses.
Retail stores.
Apartment complexes.
Construction projects.
Yet many of those cameras are still essentially digital witnesses.
They watch.
They record.
They wait.
The opportunity is to add intelligence on top of that infrastructure.
That’s where the economics get interesting.
If a business can make existing security infrastructure more useful without completely reinventing the physical environment, AI becomes far easier to justify.
The pitch is no longer:
“Buy another piece of technology because AI is exciting.”
It becomes:
“Make the technology you’ve already paid for considerably more useful.”
That is a much stronger business proposition.
AI Should Help Humans Act Faster
There is a tendency in AI conversations to obsess over replacing people.
Can AI replace writers?
Can AI replace salespeople?
Can AI replace security guards?
Those are interesting questions, but they often miss a more immediate opportunity.
Sometimes the best AI doesn’t replace the human.
It gives the human better information sooner.
Imagine receiving an alert saying something unusual may be happening at your property before anyone has called you.
Now a person can investigate.
Call security.
Contact emergency services.
Check another camera.
Reach someone on-site.
AI becomes the early-warning system.
The human still exercises judgment.
That’s a much more realistic—and often much more useful—model of human-AI collaboration.
The Business Case Is Prevention
There is another reason I find companies like Monitour AI interesting.
They sell something entrepreneurs should understand very well:
the value of preventing an expensive problem.
Preventing a fire does not create a flashy new revenue line on a spreadsheet.
Neither does preventing theft.
Neither does preventing vandalism.
But avoiding a six-figure loss can be just as economically valuable as generating six figures in new revenue.
This is why preventative technology can have such a powerful business case.
The ROI isn’t necessarily:
“We made $100,000 because of this technology.”
It might be:
“We didn’t lose $100,000 because of it.”
That matters.
Building AI Around a Real Problem
Another lesson from Xavier’s story is particularly relevant to entrepreneurs entering the AI space.
Start with the problem.
Not the AI.
There are endless startups right now adding “AI” to products because the letters themselves generate attention.
That’s backward.
The more interesting companies find an expensive, frustrating or dangerous problem and then ask whether AI provides a better way to solve it.
Property owners already worry about fires.
They already worry about theft.
They already worry about vandalism.
They already buy cameras.
They already pay for insurance.
They already spend money on security.
The problem existed long before generative AI became fashionable.
That means there is something real to solve.
From Surveillance to Prevention
Security cameras have spent decades answering one question:
What happened?
The next generation may increasingly answer another:
What’s happening?
Eventually, the most useful systems may go one step further:
What should we do about it?
That progression—from recording to detection to response—is where AI becomes especially interesting.
Because the camera isn’t valuable merely because it can see.
It’s valuable because someone can act on what it sees.
And when the difference between detection and response is measured in seconds, those seconds can potentially mean the difference between a close call and a very expensive disaster.
The Bigger Lesson
My conversation with Xavier reinforced something I keep seeing across industries.
The best AI businesses aren’t necessarily the ones with the fanciest technology.
They’re the ones where the value proposition can be explained in one sentence.
For Monitour AI, that sentence is pretty compelling:
Your security camera shouldn’t just record the disaster. It should help stop it.
That’s a much bigger idea than another camera.
It’s a different way of thinking about what security technology is supposed to do.
And as AI continues moving beyond our laptops and into buildings, vehicles, stores, factories and cities, we’re going to see a lot more businesses built around exactly that shift:
From documenting the past.
To understanding the present.
To helping humans respond faster.
Listen to the full Legacy Launchers conversation with Xavier Espinosa, Co-Founder of Monitour AI, for more on AI-powered security, commercial real estate, computer vision, entrepreneurship and the future of smarter buildings.
Legacy Launchers explores AI, entrepreneurship, reinvention and the people building companies worth paying attention to.
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