The AI Reality Check
The camera that watches the footage for councils
Jason Scarborough is founder and CEO of Echidna Cams Pty Ltd, which builds surveillance systems that do more than record. The business started with council illegal dumping officers who had given up on camera gear, and it stands out because the software watches footage for signs of an event instead of leaving people to review it all themselves.
AI has been useful for outreach research, drafting and other repetitive work, but compliance is one area where human verification stays non-negotiable. The bigger shift so far is not customers arriving via ChatGPT, but customers arriving already aware that recording footage is not the same as detecting a problem.
What’s the quick origin story of your brand, and what makes your product or positioning genuinely different from other options in your niche?
About three years ago I was sitting in a working group with council illegal dumping enforcement officers, and I realised I was hearing the exact same complaints I’d made myself over a decade earlier when I was still in government regulation myself. Same problems: it takes too much time, it’s too complicated, the imagery’s too poor quality to actually use, there are only limited cases where it can be used. A lot of these officers had ended up sticking their camera gear in storage because it just wasn’t worth the hassle of pulling it out, setting it up, and going through the footage.
That was the moment it clicked. A decade had passed and the technology genuinely hadn’t moved. So my co-founder Gabriel, who comes from robotics and aerospace, and I built Echidna to fix the part nobody else was touching. Most surveillance options on the market are still just cameras that collect footage people have to watch. We built the part that actually watches the footage for you and tells you when something’s happened.
Where does most of your new business come from today, and where do you wish it came from?
Government, overwhelmingly. Councils, state government agencies, land management agencies, that sort of buyer. Part of that’s because our platform’s genuinely adaptable. The same system that catches people illegally dumping waste works just as well for conservation, watching a remote asset, or vertebrate pest control. It wasn’t built narrow, so it doesn’t stay narrow.
Where I’d like to see it go is infrastructure and construction. Right now they’re using similar gear to what those council officers mothballed because of their reliability and operational issues.
What’s one thing you’ve actually handed over to AI in the last year, and one thing you tried it on and went back to doing the human way?
I’ve fully handed over is outreach research and drafting. Every council or agency I contact, I need to know who’s the right person, what they’re dealing with, and how to say something that’s relevant to the specific challenges and pains they’re currently facing, instead of a form email. That used to be hours per contact. Now I can do it properly for dozens of people in the time it used to take for a handful.
The thing I went back to doing myself is and research related to compliance matters. We have built jurisdiction-specific guidance on surveillance camera use, and I initially had AI research the compliance issues involved. It hallucinated, badly: cited cases that didn’t exist, got legislative provisions numbered wrong, and even missed a couple. Nothing malicious, just confidently wrong. So now everything compliance related gets traced back to the actual primary source by a human before it goes anywhere near a customer. AI’s useful for a first pass, but you can’t outsource being right.
Have you noticed a change in how customers find you or what they already know before they reach out? Is anyone arriving through AI assistants like ChatGPT yet?
Not through AI assistants, no. Nobody’s told me they found us via ChatGPT or anything like that. But what has changed is how much people already know before they talk to me. A few years ago I’d be explaining from scratch why footage-only cameras don’t solve the problem. Now people show up already understanding the gap, they know the terminology, they’ve usually already worked out for themselves that recording isn’t the same as detecting. I’m not educating them from zero anymore, I’m confirming what they already suspected.
Whilst we’re working on our SEO, we’re also acutely aware that AEO, answer engine optimisation, is rapidly becoming a thing, and we need to make sure our business is being picked up by these systems too. Nobody’s arrived that way yet, but I’d rather be ready for it than catch up later.
If you were advising someone in your industry on all of this for the next 12 months, what would you tell them to actually do, and what would you tell them to ignore?
If you’re a startup, your first job is survival long enough to get your product to market. So use AI for everything that’s repetitive and time consuming and doesn’t need your personal judgement. Research, drafting, first passes at documentation, the outreach grunt work. That’s time you get back to spend on the two things nobody else can do for you: building the product and understanding your customer.
What I’d tell them to ignore is anything that turns AI into the story instead of a tool. It’s a tool that deals with the dull, repetitive, research heavy tasks that chew up precious time and productivity, and that in itself is a gamechanger. You don’t need an AI strategy that people are impressed by. You need to ship, get to customers, and survive the next twelve months.
Thank you to Jason Scarborough and the team at Echidna Cams Pty Ltd for sharing what actually worked with Leaders Perception readers.
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