Robin Braun
speaker
100 appearances
1 recordings
1 series
first heard Jul 2026
last heard 16 Jul
Robin Braun’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.
Appearances
It's a very messy data problem.
There's handwriting on deeds, there's barcodes, there's all sorts of interesting things.
And what was interesting is that when we first started talking to them, they wanted a better spreadsheet.
And we were like, no, you don't.
You actually want agents to go and figure out your information and give you back answers to questions that you need to ask, because you're going to create a spreadsheet of a bajillion different points of light.
However, what is the actual question you're trying to solve today?
And did you capture that bajillion and first point of light that you need to answer that question?
And so it was a really great conversation that they didn't know that we could solve their actual problem.
They thought we could just give them a better way for them to manually solve their problem.
And we actually automated the complete challenge so that they now are very much, they started perhaps maybe AI reticent to now really being AI first.
But I think that was such a great difference of initial expectation to working outcome.
So with the rise of agentic AI, I wanted to take a revisit of what Smart Cities is.
We've all seen the dystopian future of these large screens looking at everything happening in the city, and we associate that with Smart City, and I use that in air quotes.
And there's a fantastic amount of safety, security use cases, traffic use cases, all sorts of different capabilities you can drive with Vision AI.
However, what we've done differently in revisiting Smart City, where it's two parts.
One is that we leveraged a backend agentic platform to be able to agentically start to connect data and processes together.
Because one of my observations is that in working with cities, they tend to be very siloed and that those silos actually prevent them from being as efficient as they would like to be, as their residents would like them to be, or as their visitors would like for them to be.
And that by creating that agentic mesh, by being able to bring that intelligence to them, it starts to break down those data silos, which allows them to consider operating in a new way.
But one of the other parts is that smart cities historically have been very custom, very bespoke to that particular implementation.
And we've really strived to create a platform where we can continue to iterate and bring in additional use cases, but maintain an integrated multi-ISV software stack on top of private cloud AI that can then manage not only today, but in the future as more innovation comes.
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