Bicycle Pedestrian Commission - Regular Meeting

Commissioner Danti?

Present.

Commissioner Present. Commissioner Sheridan? Vice Chair, Chair Mohani?

Present.

Okay. Let the rec know that commissioner Sharon and Vice Chair Kumar are Real quick. I from vice or She'll be here in about twenty minutes.

Am I

having an echo? Does anybody have their volume on?

Okay.

Anyone in person or not from the audience?

It's not good.

Yeah. My voice.

It's sounds like it's your machine.

I

don't hear it. Go. Okay. Good. Thank you.

No one's. Then we have the approval of the minutes. Right? Mhmm. The written communications? No. I approve all of them.

I'll I'll move to approve the minutes.

Right?

Yeah. You can you see us.

Right? Yeah. Yeah. Okay.

So we'll

Commissioner Danti?

Approve.

Commissioner Garg?

Approve.

Commissioner Sharon is absent. Vice Chair Kumar is absent. Chair Mulati?

Approve.

The motion carries unanimously.

Yeah. The wall pops is nice.

We have now speakers for oral communications.

K.

So next one, new business presentation on CT CT's CV technology platform.

Just a second now. What's the background on this? Is this something that we are looking at or filling it

out? They have a they will have some modules for cities, city governments to utilize and have to prepare them. That's it. On the name, they are mostly because of course, city government, city government. So

these are two demos of AI tools that chair has set

up Okay.

For us to evaluate.

Hey. Good evening, everyone. Thank you so much, and it's an honor to present in front of an audience like this. My name is Neema.

I'm Rishan.

And we are CitySites. In the next twenty minutes or so, you're gonna learn a lot more and get a lot more clarity on what CitySites does and how it's useful for the cities. So, let's begin. Every year, city governments, local governments, and city organizations spend around 2 to $3,000,000,000 on getting the right kind of data. And the two main prominent organizations which are related to Citi, which is a GFAO and the ICMA, which is the the government financial services organization, officers organization, and the International City Managers Association, they actually identify, the fact that there is an explosion of of data and and information as one of the leading causes of for cities to have budget discrepancies, overrun budgets, and have budget pressures.

So and that's mainly because based on their research, they have identified that a lot of city staff and city lay leadership spend hours and months looking for the right amount of data and downloading it, curating it, finding the right in that and analytics and metrics so that they can use for decision based decision based decision making. And so and that's how the the budget gets overrun. But where does that leave the residents? And, you know, they're wondering where their tax dollars have gone. So we're not here to complain, but then we have a solution.

We have city sites, which is an AI powered, deep domain expertise, which curates and finds all the terabytes of messy, city domain data and curates it and delivers it in a matter of minutes, what normally would take months, just because we have a proprietary algorithm at the background that is running. And then we make sure that the data that we get is of different sources, but all of them synthesized and curated at the same time. So we deliver what would take months. We'll deliver in in minutes. So what results is, you know, cost efficiencies.

What results is operational efficiencies. And the real time dashboards are amazing because it tells residents exactly what the city is up to and resulting in unprecedented transparency and which really builds that trust between the governments and the residents that it serves. So we're not just a report that collects dust. We are an organization with an AI writing an AI layer, which the cities can use to make smarter decisions, you know, using technology that they're already aware of. So I'm excited to show you what city sites can do and make it real, starting in California and scaling it nationwide.

So let's begin. So our mission is to curate very complex data that is related. So, for example, the census data, the EPA data, the a q AQI data, public safety data, political data. We take a lot of disparate sets of data, terabytes and terabytes of it, and then we synthesize that, and then we provide meaningful metrics and analytics in a matter of minutes. And so, again, you know, it it is resulting in our fiscal efficiencies, and we can put a number to it.

We you know, based on our research and the white people that we have produced, we feel that it is and we have seen that it really saves about 20% of the outsourcing cost. And if it is a matter of in house production of any kind of data, we would save about 20% of internal resource cost and productivity. Increasing productivity were almost 50%. So let's look at the that was at a higher level. Let's look at a little more closer level.

So here we are having all kinds of fragmented data systems, which caused the bud budget pressures according to the GFO AO and the ICMA leading to budget deficits. And either one of the two things happen. You either go into, you know, consulting mode, and that's how you spend 2 to $3,000,000,000 per year, or you are overloading and work overloading your internal staff. So what happens when you use city sites is that the algorithm that uses domain expertise you know, when you're talking domain expertise, we're talking urban planning, we're talking finance, we're talking, AI, we're talking data science. You know, we're using all these domain expertise to come up with a proprietary models and proprietary algorithms.

Make sure that we're not losing any sensitive data because cities have sensitive data. The staff data, the resident data, we don't touch any of that. And we also do not introduce any kind of bias into our algorithm in the models, so we can be rest assured that it is it's very cautious. I do have that small clip at at the bottom, which is basically a white paper from the GFAO and the ICMA, which which tells what I've been saying, which is, you know, the reason for one of the main reasons for budget deficits and budget overall is the fact that data is very difficult to process for, the meaningful decision making. So the future with city sites is good because, you know, we are giving you, something that will increase your productivity, increasing your cost.

And at the end of the day, we're saving hundreds and thousands of dollars for each city depending on what kind of work they're involved in, like data and metrics at your fingertips. So this is why I wanna spend some time. Because on the third column, you see strategic vision framework, which is adopted by city of Cupertino. So what I wanna tie over here is what are all our products? What kind of value it brings?

But what exactly which strategic initiative from Cupertino that it relates to, and how can you actually use it? So one of our is it getting cut off? So the first one, the placemaking and the community investment tracker that we have. Now urban planners will tell you very quickly what placemaking is. It is basically all the investment that the city has that makes a city more livable, more enjoyable, and attracts more residents and businesses alike.

So what are the investment dollars? So, you know, for example, parks, trails, events that the community gets to engage more in and other in public safety. So these are all the investments that go directly to place making. It's also sometimes called generally beautification of the city. So we're having a, you know, a a place making and a community investment tracker, which you will see down, you know, just in a few slides below, Ushan.

I'll just wanna get to you. And so it basically promotes community engagement, and then it also it's a huge factor in creating vibrant neighborhoods. And what does it really do according to your strategic vision? It also you know, one of your big initiatives is public engagement, resident engagement. So that would really enhance under, you know, the tracker when when people can see what kind of investment Cupertino is making.

And you can see, you know, once we show you that Cupertino is really doing pretty good compared to the other cities. So where can you use it? You can use it you can use this tracker on your website. You can use it for discussions with, you know, possible businesses that wanna move, and they're looking a pizza as a plea a pizza franchisee who's looking to expand and considering maybe Cupertino and considering Sunnyvale or considering, you know, the neighboring cities. And then, you know, once you can show them, hey.

This is the investment we're making. This is the investment we're making in the community, and we have a higher potential for your business to grow. And so these are the edge that this is the edge that you can use, in these kind of, like, situations. In, you know, councils like this, in in planning council, when you have a lot more residents come in, so we can show them that this is what we're investing in, which will actually, you know, increase their trust in the government. So the next one is the and affordable housing direction.

So you please move it so we can see that? Because the products are I need

to see the left column, leftmost column. Or so let's shrink it and make it, like, 90% or so.

Okay. Just just not with this one. Let's not do this. Right? No. Go ahead. So is this better? Yeah.

Yeah.

Yeah. Okay. So we have and affordable housing. So one of the again, a key part of your strategic vision framework is having balanced housing. So what the the does is it get it gives you details about what kind of housing that you have.

And so the mix, you know, how many are renting, how many are owning, what kind of, you know, the the people's income. So then you can identify the gaps. And if you are trying to have more affordable housing, that's a way to make a case to the public saying this is how many affordable housing units that you would want. And it's a real time dashboard because anytime you are having, any, updates, we will be able to update it. So based on, you

know, how First one is called what? Placemaking and community

Placemaking and community investment.

Placemaking.

Yeah. So yeah. So this would be something that is very key to Cupertino's strategic and and and initiatives and also addressing homelessness. So we can clearly look at the census data in this case and find out, you know, where are you know, what is the population? What is your floating population?

How do you address the homelessness? So all this data is available to you, and so then it'll help you make the real time decisions and faster decisions. So the, the next one is the budget tracker and benchmarking. This is something that'll be very valuable to all the departments in the city so that they have, goes right to the GFAO and the ICMA best practices when they say that having that and continuously monitoring that would help you maybe not have the budget overruns to that extent because you are constantly knowing, you know, where you are, what is your run rate, how much more do you have in your budget that you that left rather than operating the dark. So, that is something that, you know, everybody can use in all the departments.

And then if you use it on the Citi website, that will give you an additional layer of transparency to the residents, knowing exactly where there's where their dollars are being spent. So the the fourth one is is a custom our flagship product, which is the the CitiSight's AI agent. We call it the CitiBird, knowing everything. And so that what you you can ask any question to CitiBird, and then it will, you know, it will synthesize the the answer and give it to you. It is very custom made made for cities, and it's not the same as you would ask JackGPT or Claude or Brock because they are looking at worldwide data.

But here, we have data which we have very, very specifically taken and synthesized. So this agent is only referring to that data, so it gives you more meaningful data. So I will transfer this over to Isha, and he will actually show you some of the functionalities.

Yeah. Perfect. So as Nima was saying, we have here is our dashboard, and we have some KPIs at a glance for you. So the first thing we have here is our city site score, which shows that, you know, it's actually in the top 88% of country, as well as right next to it. We have place making investment, which we calculate to be around $660 per resident. And you might be wondering, like, what goes in to calculating that score.

Yeah.

Can you zoom in? Yeah. Oh, yeah. Presentation mode. Try that, mister Dan.

Better now. It is. Yeah. Yeah. You guys might be wondering what goes into that, and it's a multitude of things such as public safety, schooling, community development, parks, and so forth. And then which leads me into the next thing, the climate action plan, which is similar to the place making investment in that it uses the parks, the community development, as well as climate programs in order to get a number from you guys. And then finally, have financial health, which takes your budget data and compares it to cities all across the nation. You'll be able to see and benchmark it comparatively to those other cities. And as you can see, the casino actually performs quite well on that.

Congratulations again.

And the

pink thing, you guys have this AI budget agent. And so instead of sifting through hundreds of pages in PDFs, scrolling in, you'll see thousands of lines of Excel sheets. You can type to this agent in plain English, and it will come back with with whatever response you like. And furthermore, we have taken metrics from many public data sources. We have bucketized it for your convenience.

And the buckets would be economic, environmental, social, and political. And we have many more metrics to show, but talking with city managers and other city leaders, they liked having these specific metrics on there. But once again, a dashboard for city insights, it's all custom made and tailor made. So whatever you want in your description can be uploaded to the dashboard. Now for benchmarking, another feature is that we can do peer comparisons.

So in case you're wondering how another city similar to Cupertino was doing, so in this case, San Ramon, you can see it in a head to head version, like, where there might be discrepancies, what they're doing better, what you're doing better. And you can see just where the differences lie and maybe implement them into the next fiscal year. The next thing we do is brand matching. So with our AI agent, we're able to query a multitude of things, especially with planning initiatives. And especially with the budget overspending, brand matching comes in in help, handy. It's very helpful because in case you need some extra money, instead of spending man hour just looking for relevant grants, we give it to you instantaneously. And so just

Normally I mean, just just a small I used to help with grant applications with my previous job, and I know it takes weeks and months to find the, you know, the right grant because there is so much information out there. And we can give it to you in minutes. Just saving weeks and weeks of of work.

Furthermore, on the resident side, it gives you a city sites placement score. And as you can see, for residents and small businesses, it's in the top eighty ninth percentile, which is very attractive to future residents and future businesses wanting to come into Cupertino and start a life here or a business. Next, there is the RHNA real time dashboard. So as Nima was saying, let's use see into projects as well as very low income, above moderate, and it gives you data on all these housing units. So you can see just how many on your owner occupied payments have a vacancy rate, your annual tax per home, things of that sort of nature.

And then finally, you're going into the budget tracker. Now looking through hundreds and hundreds of pages of PDFs, it can get kind of tedious looking or trying to sift through and see just what exactly each overall department has. But this gets it to you right in a clean, nice table. You can not only see the overall budget, but the budgets of every department as well as the effective run rates. And not only that, going back to pure benchmarking, not only can you pure benchmark versus a singular city, we can pure benchmark versus all the cities in our database, but specifically for cities that fit not only your budget, but your similar size too. So stacking up Cupertino versus the top 75 percentiles, see that Cupertino actually does very well against them.

Yeah. And we have used thousands of cities all over The US to come up with this pure city combination. So you're making sure that when you're comparing Cupertino, you're copying you are comparing almost apples to apples and where does it stack up. And so as you can see anything in the green, you're doing much better than something a p or a CD, which is almost like a, you know, the the the the golden CD, if you will, compared to, you know, which is computed from thousands of cities all over The US. And some places, I think, are doing not so great.

But this is something that, you know, city managers and city leadership can go see, look, and say he and start wondering, you know, if there's something that they need to be rectifying. So you're not working in the dark and then, you know, you're making informed decisions as to where we need to be working a little more and where you can back off a little more. So it'll help you focus on the right kind of resources. So this is an example of what our AI agent can do. And I just wanted to give you an example because I think the city of Dublin had an initiative for on from the public safety side that they wanted to use AIPRs and sit camps all over the city to improve public safety.

So that that project I mean, this is all information that I've got from the Internet, and it's not from exclusively from the city. I think it's public information. So I think it's what the, you know, the main project started off in 2024, and the implementation was something in 2025. They're still extending it. But the fun part is what I wanted to wanted to dwell on because almost, for nine months in 2024 is what they took to come up with, how many sitcoms that they need and how many ALPRs they need in the city and where they need to be placed.

So that's nine months for you, almost nine months for you. So the same thing, we queried with city sites. And in three minutes, we got an answer, which is pretty close to what they ended up having and deploying with with the and then they spent around $3,000,000 for that project. So we would have definitely saved them about 20 to 20 actually, more because it's almost 30 to 40% of the time that we could have saved where they could have started off at a higher level and said, okay. This is where we can actually give you also where to place them.

So a lot of the project would have been done already. So when they they hired their outside consultants, they start off at a higher level and but a much lower cost. So that's the the fun part. So we not only give you the details of, like, what the, you know, the solution would be, but then would also give you actionable plans and also a downloadable report that you can download and then start working from there. So instead of starting at level zero, you can start off at level four or five.

And so that's where the savings actually comes from. You know? Savings in productivity and also savings in cost of outsourcing or internal, resource costs. So and I do wanna emphasize on the fact that, you know, we are having ethical AI. Because we're using all publicly available data, there is absolutely no sensitive data we touch.

And we do not need IT integration because this is not something that, you know, we are using any of the Citi's internal systems, so we don't need to integrate with the Citi IT. And it's ethical because we're not introducing any kind of bias in our models or in our algorithms. We don't introduce any kind of bias. So you can be assured that whatever you're getting is truly something that you would have worked on for weeks and months, and that we're just giving it to you faster because of the fact that we are curating it with the help of AI. You know, we're not the magicians here.

AI is. And the fact that CD size is possible today only because we're using the power of AI. But what we've added on is an extra layer, of course, is the fact that, you know, the domain expertise and the and the proprietary algorithms. You know, one adviser is sitting right here. He has about 300 patents in that space.

So, you know, he was advising us on what the innovative component is, that can go into this. So that's the whole magic portion there. And, so I just wanted to really emphasize on this one. So the key takeaways, is, you know, based on our research and white paper and, the research done by, you know, the best practices from many organizations, we will very comfortably say that we are able to deliver around 45% productivity in terms of, like, either reducing costs or internal resource, you know, taking the load off the internal staff. We are not saying that we do not have to hire consultants, so we're not saying that the staff need to be laid off.

We're just saying we'll make the work their work easier to to we take off the drudgery. And so even in terms of, like, outsourcing to consultants, we give them and so starting it around zero, you start off at a much higher level, thus saving consulting cost of us. Saving the fee money and then translates to resident satisfaction automatically. So and the whole thing is because we can give you everything that is relevant in terms of metrics and data and grant information, budget tracking, and all these other good things in in the matter of minutes and stuff else. So thank you all so much for, you know, being our audience today that we could, you know, tell you more about city sites.

I deeply appreciate this opportunity, and we would love to partner with the city of, Cupertino so you can see firsthand, experience firsthand, and, to leverage firsthand the everything that city sites had to has to offer. I also wanna especially thank Lindsay and and Marilyn to help us set this up. So thank you, and we're open for any kind of questions that you might have.

Thank you.

So are you currently working with Citi

now? We're at this point, we just 15 ago is when we are all set and we're ready to, you know, send out the pilots. So what we did, however, was work with a lot of cities to get the voice of customers. So which means, like, you get their feedback, what is important, what is not important of everything which went into these products. So we worked with a lot of cities around the Bay Area. Mayors, vice mayors, council members, city managers, financial directors, we worked with all of them. And, yes, and everyone was very excited about everybody. We had just started off, like, implementing it.

And I'm I'm curious because you're not using city data. You're using public data.

Public data. So what public data are you using? So we there's plenty of public data. Like, census data is one, which is, you know, huge that, you know, every the backbone of almost every city decision making. We also use EPA data, AQI data. We use public safety data. We also use budget data, which is public data for all the cities, so to name a few. And then we have, yeah, a few other datas.

Yeah. I I just I mean, if we're gonna put out those kind of numbers and show Cupertino in a certain light, we would need to know exactly where that data is coming from and how it's being calculated. You know, your example of ALPRs, you know, there's a a good analysis that we needed those locations, and we have to do our due diligence to ensure that we pick those locations. And and again, that's the sheriff's office, so it's not necessarily Cupertino. But I'm just saying, you couldn't just do an analysis and say, okay.

The AI said this. You know what I mean? Like, you would need to have some good details as far as exactly how that analysis was done, what data went into it. I mean, that's there's a lot of of factors there that people aren't gonna just rely on on on, you know, an AI that, you know, has a a magical, you know, answer. So I I just think that, yeah, you definitely need just a good understanding of what what is going into these tools.

Absolutely. And that that's a really great So I think in the Dublin example was, you know, to to say that we start off at a higher level. So you start off with, you know, an analysis of, okay, we need 82 ALPRs, and we need 32 sit caps, and these can be in this location. Then afterwards, you get to take that and then do your due diligence and say, okay. Is this, you know you know, is is this viable?

Is this viable? So you don't start off with, like, you know, a nine month study as to, like, oh, where do we need? So that's what I was trying to say that you start off at level four and five instead of at level zero, and that's where this comes in because it really speeds up the process by, by giving you that kind of information. As far as, you know, the sources, we will always be giving you the sources as to where the know, where are we getting this information from so it can be

So, yeah, I just data is so hard. Right? I mean, we do it all the time internally. We're building our own AI AI agents, and there's a lot of massaging that goes into these datasets to make sure that you're getting a a good viable answer that that, you know, you can replicate in in your it's just pulling in all of these disparate systems. Would just be I would just wanna, you know, make sure that we're getting, valuable data, you know, like, accurate valuable data.

I think that's that's the key part, right, is ensuring that whatever's going into it is actually, and what we're seeing as a result on these dashboards is is, you know, giving us data we can rely on and that we could feel confident about saying that you know?

One of the things to identify hallucinations, for example. Right? So you can with AI, traditionally, you get hallucinations. So one way to avoid that is ask you to do retrieval augmented generation where you have your source of data which is multiple times curated, and you are only looking from there and not from somewhere else that you have learned. Right?

So that's one way. The other way that we have found to be quite useful is stream of thought. So you if if you have a logic, you go through that logic step by step, evaluating it and giving you the results. So you you go to some of these additional tricks on top of massaging of your thing, massage the data as well. But still, the logic needs to all well connected across and all has to make sense.

Right. Right.

Yes. And so

And being transparent about it as well. So that's the final thing that will convince you is to show you on the steps. All things are not just yeah. Trust me.

Yeah. That's the part I would need to see.

Right. Yeah. Have a couple of questions

about that too because sorry. I know I'm late to the party, but it seems like ethical AI and ethical development AI, like, development and data sourcing is very important to you based on the the bits that I caught at the end. But I also and I'm sure you put lots of work into it. I'm sure it can tell you're very proud of your your proprietary algorithms, all the stuff that you put into it. But you said you said a couple times that we make sure to completely eliminate bias by only using the public data. How do you square that goal to eliminate bias with the introduction of, as you said, massaging the data and proprietary algorithms that could potentially introduce some of that data back that that bias back.

So

Yeah. So one of the so this comes in the red box responsible AI. Right? So the bias is usually, it it creeps in in the system when you have a majority and a minority, and you train the data on majority. You even when you are doing the duration, you only focus on the majority because that that's what you learn.

In in our scenario, we make sure that the data is balanced. There are statistical tests that are done to ensure that you have a balanced data and based on those, the decisions are made and not just all the data that you throw in there. Because then minorities will have no chance of succeeding in in in a scenario like that.

Thank you. Because, yes, as you mentioned in some of my work, you and there can there's also underrepresentation in the data Right. Of the minority because of the lives because you get you get that statistical sample, like, virus even when we attempt to take all the data as it would to

Take as is, then, yeah, we will turn into the majority bias. Yeah. Under the big big name and then whatever data items will have that built in. So we take a lot of effort to balance the data. Data balancing is one of the critical ways you can especially when you are using things like that, you want to make sure that this is seeing the balance data.

So I know, like, did you have a couple statisticians working on the problem, presumably?

I have sent the whole entire slide set to Lindsay.

Okay. Awesome. I'll take a look at

this. Yes.

To this forward. Yeah. So the city of Dublin that we were working through their data also.

Now we worked with the city of Dublin just to get their VOC, you know, what was important, what is not important. We have not deployed our solution to to city of Dublin. And this was in retrospect, you know, that, you know, I wanted to draw the comparison.

Okay. To develop your proof of concept here.

Yes. Right. Exactly. Exactly.

Did you deploy it anywhere?

Oh, no. We just started. You know, like, we it's about fifteen days since we've actually completed the product, the MVP, and the, you know, the pilot is ready to go. So we are just starting to talk to a lot of cities to, you know, set up and then, you know, just to, you know, give the demonstration and then see if we can get on to a pilot. So that's that's the answer of all all the questions that

What's your oh, sorry. What's your business model? How do you what's your licensing model?

The license model is a is a subscription based.

Subscription for the CD as a whole?

Or For the CD as a whole. Yeah. It's like a like a 100 licenses or, like, you know, 50 licenses.

Is it by user or by city population side? Per user. Per user.

But your data can your application can also take the proprietary data of the city and. Your application can also like, suppose you are doing a trial with CTO of Coperty. You can take that data from Coperty. And process it. Yeah.

Mean, if you're referring to, like, something like the budget tracker where, you know, every department can upload their own budget, then it would be a lot more, you know you know, the run rates are going to be a lot more real in that case because this is a general run rate that we have, you know, a linear way that we have computed because without not knowing exactly how much each department and Cupertino has spent already. So, you know, they can they'll be having a way to upload their own budgets so that they are having that clarity as to, like, how much they have spent and how much what is the run rate left.

We have all that in the website. Yeah.

The budget book's

on the website. And All the cities have the budgets on the websites. Yeah. Yeah. But I don't know if you have a budget tracker or not sure if you have a budget tracker or

We do. Yeah. We have online transparency tools that allow you to go in and and analyze the budget data.

Like OpenGov, but OpenGov doesn't compare their data to it's only one city with

Exactly. Yes. Great questions. Thank you so much. Yes. Thank you. I do. Appreciate it.

Chair, can we go to public comment?

Yep. Public comments.

We have no speakers, chair.

Can we forward their presentation?

To the To the commission. Yeah.

Okay.

Thank you very much. We appreciate it. Thank you very for tuning in. Thanks so much.

Thanks. Alright.

So next step.

Name is by completion.

You're on. Yes. Yes. Please. Yes. Definitely. Thank you so much again.

Thank you.

Thank you

for coming. Nice meeting you.

Would I be contacting just in case you

Contact me. Okay. Yeah. But you have Marilyn's contact. So We do have Marilyn. Yeah. So we'll go through Marilyn. Yes.

Thank you. Thank you so much.

Thanks, everyone. Thanks for giving me this offer.

Everybody knows what I do.

He was commissioner. I used to be commissioner previously from 2020 to 2024 in this.

Ah, thought he's

a lawyer.

So So when I talk to him, he says, oh, yeah. Yeah. And I do. I have all the. So I I

do have some buyers because I am from. I've been living here for over twenty four years, and my cofounder is also a resident for over two decades. And given that I worked here, I would like to continue contributing to the city and whatever means and whatever in my life that I do. So as a cofounder and a CTO of Cyphus, company is actually registered in Sunnyvale, but pretty much all the things happen here in the city. So we would like to bring in present and see kind of where the innovation is happening and what could be a possibility for our city to explore as we live and breathe.

Right? And pretty much like any government or a commercial, we do consume the technologies, and we do consume commercial technologies, and we continuously look at the avenues to optimize and do better. And, on the other hand, cities also grappling with the ongoing cost escalations and, budgetary constraints and, ongoing struggles to how to meet all the things while, continuing to serve the company. So I as a history for myself working in a technology where

I

was a CIO and CISA before, managing a startup I mean, IT and people technologies in the small startups as well as some bigger companies. And also, cofounder, she worked in a company where she managed large projects that are integrated. I mean, if you really look at, for example, very, very mature technologies. Companies have been there for about couple of decades. They have accumulated enough customers.

They have matured enough. Still, if you really have to bring four or five different tools together and make them work, they don't necessarily work. You end up building your own team of a dozen people, spending a few million dollars, spending about an era or two to actually get the value out of those tools. I mean, I typically compare these things as, like, if it is a car company, if you're trying to buy a car, you're basically getting a kind of a bare bones car without having any nice features, and you have to take it to your service center to make it work. That's not how you buy the car, but the technology has been that's like, typically, you buy a tool and you bring an implementation team, and implementation team would spend about months actually making it work for you.

Now how is that a a what you call, like, a finished product? Right? We don't necessarily accept, But that's how the technology has it. And, course, you can challenge it by your premise and say technology evolved so fast. And often vendors actually deliver it half baked and then let the partners and actually go and implement.

And typically, what we have seen in my experience also is that if you spend a dollar on the tool itself, we'll probably spend about 3 to $4 implement and actually get the value out of it. I mean, that's not typically how the the end products that we consume. Right? So with this kind of a experience, we really wanted to flip the thing and say, when you buy a tool that really is supposed to sell you, your implementation cost should not be anywhere at fraction of that cost. Right?

And that led us to build this foundation. Once we built the foundation that actually enabled us to build any number of tools and technologies that any business, any service organization, any government consume day to day. In this case, obviously, we're talking about HR, IT services, and CRM, or any ERP solutions. They're all there. We are selling some of the customers and some are 40% direct customers.

And we also have some partners who actually deployed our solution on their own public cloud as well as their own data center or perhaps on our own cloud and be able to white label and serve their own clients as well. And we have a whole 5,000 end users consuming this technology, and we are globally spread out. We have few customers in India, a couple of our Pacific Islands, and a couple of them in US as well.

So What kind of us?

So we do see a pattern of telecommunications kind of a tier three, tier four, our telecommunication service scores, ISPs, and our Pacific Islands, where they have automated all their internal tools, one of the case studies we will see over a phone. I pretty much consolidate all of them into our platform so that these departments don't have to depend on the IT and say, hey. I need a help. And you actually file a ticket, and the IT may take their own time. And in the process, you're basically your backlog keeps growing.

Right? And today, HR department pretty much manages their own work. They never go and knock on IT department. Finance department, they pretty much all process all their payrolls and never go and talk to IT. There is no need for it. IT has their own purpose in the business. They do their part. Right? It's a engineering service and it has a telecommunications. But when it comes to this business functions, whether it's HR, CRM, or payrolls, finance, accounting, you don't need to go day to day and say, hey.

I need to do something. Can you help? Because what platform also does is gives you a any business user to actually configure the way they want it as opposed to business user force it to fit into those platforms that are made today. Right? That's a picture. And that's the premise, and we have built it, we've been delivering it. And I would like to give an opportunity and see if there is a need or a technology team and definitely explore and take this.

So just to be, you know, direct with you, we we just are implementing an ERP, and we literally are completing the contract. It's going out for signatures in the next couple of days. So, you know, it's we're not looking for an HR platform. You know, if it was, you know, tools that helped with specific things with HR that maybe the platform didn't currently do, then that would be something that we would explore. But but as far as, like, an ERP, we have that covered.

Right? We've spent a couple years now getting this new replacement ERP system approved and, selected. It's a huge process of of going through that, and and we're finally at the finish point where we're about to implement. So so we're not exactly looking for a custom ERP solution at this time. Right? But if you had pieces that, you know, AI tools that were helping with, you know, procurement or HR, like, specific things that could be time savers, then that would be something we would explore.

Absolutely. Thank you for filling in. So, typically, anywhere we walk in, we don't expect that it's an empty slate where you just start up the tool and set

Right.

What we call, like, a green environment. Right? And the life is that there are already tools and that there's data and there's processes that are serving the community. Yeah. And at the same time, as I said, is one URP tool, if it took, like, a couple of years to bring it to life, then that really speaks of the current complexity and implementations and all those things. Right?

Yeah. Just just to clarify, it was two years. They haven't started the implementation. That's the city

Oh, the requirements.

Assessment of what we have. Have.

Sure. Sure.

Yep. Yep.

Proposal. Yeah. Going to asking for the Yeah.

Yeah. Got it.

Yep. Yeah. It's a long

It's a bit off front.

Implement this, it would be another two years.

That's the difference. If if the tool would take two years, we'll have some metrics that would actually probably take a fraction of the time.

No. I mean, in a first to buy any tool, it takes two years. Yeah.

Yeah. Yeah. The typical time for a purchase process purchase process, it's

It's faster.

Purchase process. Yeah. I agree. I agree.

Yeah. Also, buying takes two years.

Typically, mean, so if you really have to do upfront assessments and comparisons and all sorts of Yeah.

Yeah. Those are the those are the hurdles that government has to go through.

Everybody has to go through.

Yeah.

There is no free money there.

Right. Exactly.

If you work in the building.

Yep.

And and so absolutely. As I mentioned, if the there are systems and there are gaps and there are difficulties, absolutely, this platform can bridge those gaps and connect with the existing systems and be able to give you power to drive the value out of those systems.

Okay.

But, clearly, you know, if you have to just go and bring other integration players to connect with these systems and give the value because the integrations I mean, the way I look at it is you have a number of these vertical pillars

Mhmm.

In any environment. Now, typically, to connect these things, you bring it an integration layer. Right? Integration is not cheap. Yeah. That takes its own cost Yes. And its own life cycle. Yes.

It may

bring the value out of.

Yes.

Now, every vendor is bringing their own AI on top of it. Right? That doesn't necessarily mean that the underlying in pillars, costs are not going away. They're still there. Right? Yes. There is some new value they're bringing. They're also, at times, adding more cost because they're now saying, oh, we are bringing AI. You need to pay for it. So those are the things that we are trying to address and say, hey. So you really don't have to take so many of them and bloated IT organization. I'm not saying that the IT organization don't have relevance. They do absolutely. But what is the optimal value that we really need? So that's the premise and how we build the platform and and then link any type of business.

And anything, for example, if you are a a you have a non IT person, with a little bit of a help, you'll be able to, in a secure manner, plumb the tool and get the value out of. Okay. That's the kind of a sophistication the platform is.

Got it.

So if there are some gaps, yes. We have we can fill those gaps.

Absolutely. So for example, if if customization or a building custom value based on existing tools itself may take a few months and lot of money, you can probably explore with this also. Because we allow you to connect with the proper authentication system and extract the data, and we don't necessarily sometimes, you don't have to copy the data. Where the data sits there, you connect the data, and you drive your whole workflow, and you get the value out. So we have also create

custom solution for CTO that need. You can also

Oh, absolutely. Absolutely. Yes. So so it's not just a product. I mean, so you can buy the services. If it really comes to the implementing this whole thing, we can absolutely do it.

It definitely would be down the road after we get

Yes. Yes.

The would be all No

expectations at this point, but presenting if there is a company and there is a team here in Yes. Account, we walk away from them.

We we appreciate it. Thank you very much for presenting and for showing us what you have.

So I have a few slides. I mean, if you have some more time, I can just walk through. Sure. I think I pretty much laid out the story why we built it and how the history has been in the IT and the number of tools that are there wherever you go. No bias for towards or against any of the vendors that have been listed here.

But I would say some of us probably have worked in any of these companies too. But that that's been the history and the evolution of technologies. And as you see on the left side, any implementations would typically take months and number of different there and the the time it takes as well as the efficiencies, particularly in the last two decades or so as we have seen the cloud adoption. And as you keep going and buying these tools, the utilization of these tools are not really so great. And there is lot of inefficiencies that have been accumulated over time.

And, so if you really think about all these things. Right? So fragmented data and multiple systems and undocumented workflows, hidden decision logics, legacy systems. You bring all of them together. You have one place where you can query the data and extract the value out of. Now, for example, at the bottom, so we have a we are also bringing AI. I'll talk about how our AI differs from the existing AI stories. Right? I was mentioning. So in this case, say, if you ask the query and say, payroll increased by so much, and it would actually extract the data out of your and present the data to you.

So you don't really have to think about how to write a query and then extract the data. Now so why and what our platform is? As you see, there are a number of the Legos or perhaps the tools. Right? HR, ERP, payroll, CRM, finance, and approvals, workflows, and any custom contracts and all those things can be plumbed on top of this.

Has have you worked with any governments? Because governments have a lot of regulation around employment, benefit. I mean, all those different factors where a lot of that is already built into these Existing. Existing government ERP systems that are really built for what we do. You know, this this definitely seems potentially more for smaller companies or even bigger companies, but that don't have as many regulations and and specific

So I will do one example here is, at least, there are two agencies. One is obviously local telecommunications partly funded by New Zealand government. And there is actually an airport authority who has also implemented this solution. Okay. And they have some policies and practice and regulations. And but, yes, definitely, we have a lot more sophisticated and a lot more complex rules and all those things.

Yeah. Yeah.

So what by the way, so when it comes to the platform itself, we do have ISO 27,001 and GDPR privacy and for compliance that's already home. So one thing I I wanted to mention this here is when we talk about all these tools, when mentioned about the unified data layer so that you don't have the data sitting in fragmented systems. Right? You all have one view, one data, and based on the user role and business function, you enable that activity that can be done and drive the whole production. And so the feature of the system is that, yes, like a traditional systems, you don't take a lot of time to actually go and plumb these things and do custom programming.

This is actually pretty much all visually driven. So business team can actually adapt an existing one and customize to their own needs. Or if you really need a custom application to be done up there, completely new one based on the existing tools and data, we can actually actually drive that most of the time with visual driven. So there is no program at all. Now with all the What? Visual. Actually, what we call the no code platform. Right?

So No code.

Code. No code. Yeah. Don't write the code. We don't generate the code.

Payment. You will generate all this.

We we never generate the code at all in the platform. It's truly data driven. So in terms of value, obviously, we have some metrics. As you can see, the workflow's done much faster and lot more operational efficiencies that you see. And real time decision making because, you know, all the data in one place.

You don't have to go around hunting and integrating and connecting some of this. And we have we do have the mobile applications as well. So comparing with the traditional systems sources of our system, obviously, are number of metrics and values that we bring. As you can see, the current systems that if you have to implement it take months, whereas we can actually bring them to life in weeks. And who builds and how it can be done?

We don't really need a dedicated, highly proficient, high cost technology teams. Business teams can pretty much customize them and actually plumb them. And coming to the AI integration, I will have one slide that that will expose exactly how we are bringing AI, but it's already there. And system architecture, I as much as the existing systems have been built in the traditional technologies, that's actually a learning lesson for us to actually how to do it differently. That's when we brought the new system in.

Right. That really enables anything can be a an application layer and applications can be composed in a modular way while having the data at the same, as a unified app. And all of these things actually bring lot of cost advantages as well as data security because you don't have a data spread out, and you don't know exactly which system is being accessed and all the additional security layers that you could bring. Right? All those things gets different.

So this is the scenario probably I was mentioning about Vodafone, Cook Island. And they have replaced six different systems that were kind of a obviously, some of them are for legacy. And some of these practices were manual, and they were dependent on IT teams. And as you involve people, there are errors and human errors getting introduced, And all of them are removed.

Okay. And

there's another services company. They have benefited by automating all their internal process. It's a very.

What are.

This is what are from Cook Island.

Yeah. I I just can't help but notice that the city of Cupertino has a has a population five times the size of that of the Cook Islands.

Yes. Population? Sorry?

You knew their population. Yes. Okay. I might be slightly might be slightly underrated. We're, like, 75. They're, what, like, 15, probably? Maybe 20. Yes. I'm not a good 20. Maybe we're only three times the size. Right. But, like

Yeah. But but it's actually now the CEO of order one cooker and actually challenged the parent company when Tigers actually demonstrated now everybody else is following.

I'm mostly surprised with the Cooker and sister own telecom company.

Yeah. 70,300 people.

Yeah. Oh, thank you. 7,000.

77

Oh, 17. Was thinking, okay. Well, it's a lot

smaller. K.

So, yeah, I I pretty much spoke about the the benefits of the platform that brings the application building and delivering the value. And that's the summary. And so regarding the AI, I wanted to lay out where and how we do things. As you can see, the top left, the Cypher's code is actually a traditional transactional system that is not touched by AI. When you talk about the data, data has to be deterministic.

I want to make sure that accuracy is still maintained. Right? Maintained. But we do use AI driven tools for all our development where they actually bring the value,

and that's all the it just the tickets.

Yep. Now the second one is the AI driven analytics. Obviously, when you present the data, that's exactly where the, plenty of the value that is driving in the society today is by reasoning your data. Right? And the analytics and insights are absolutely great value, and we are often.

Now where else AI can also help is AI is actually giving you the workflows. When you have the data trans with the data on a stick foundation, now you enable in a solution layer the workflows that that actually is done by AI. Now what else is possible? We're also presenting the data as you consume. Perhaps you can bring your own AI model keys if you already have them, or we can offer the keys.

And at the end of the day, we can present who is consuming how much, which tool is consuming how much, and what time frame so that you get the visibility of it as well. So that's the presentation.

Thank you. Any questions?

Anyone else? No. This is not my core strength. So

Not my core Sorry.

Are you talking? Did I interrupt you?

What's that? Did I interrupt you?

No. I said not my coach strength either.

I see. I just wanted to check and make sure that we went to public comment.

Yeah. In public comment.

We have we have speakers. Okay.

Thank you.

Yes. Thank you very much. Thanks for coming. We appreciate it. Yes. Nice meeting you.

Nice meeting you.

Now we move to permissions, head up to the work plan. Right?

This is very tiny to read. So we do have to review the work plan. Oh, okay.

Thank you. I know this is the default font size. Yeah.

This is what we had gone through last time. Page 13 of.

Yeah. I agree with you all.

Sorry.

Is there a quick question. Is this a right time to ask? Sure. So is there a a safety initiative for the council or is

Where do you see that?

No. I'm seeing here public engagement and transparency. I forgot what the different council goals are for this year. For the cybersecurity event? It's categorized under

Yeah. Under public engagement and transparency. Yeah. Yeah.

I I think the public engagement part applies here. This transparency is, no dollars and no dollars.

So are we good with this, or we want to make any changes? Good.

Yeah. It looks fine.

Can we go to public comments before we close the item?

Yeah. We have when we were drawing that cyber security. Yeah. You have the Yeah. Yeah. Public comment

on the items.

We have no speakers here.

That's the next

Yeah. Just to note, you know, clarify on the owners while you are doing server. And then it's because of AI. What do

you have created subcommittees, share your

Yeah. That. So the cybersecurity subcommittee, the the event committees?

That's Sudip, the vice chair, and I. Yes. Yes. Send us our

security subcommittee. And the robotics. Hello. There anybody else? And you are planning to create a new subconscious for that? I can.

I was in the subcommittee of that.

It's like

the No.

We know

that. We talked about it.

Or what What about it?

Yeah. No. We didn't create.

Subcommittee.

We didn't create. Oh, we didn't create it. No. No.

Only subcommittee we've created was for the cybersecurity.

And and then there is a accurate and it does implementation. So

is this more, like, bringing ideas? No. Okay. But okay.

So They have an event.

I think they've been doing that, right,

like, with the

four presentations we've gotten. I thought the four presentations we've gotten were

Submit that.

The one item. I thought that was the idea. Am I misunderstanding?

Oh, you

That was my thing

too. Sorry.

That same

You don't necessarily need to over subcommittee which had those presentations. They were all related.

All good. Yeah.

Okay. So then we'll move forward with cybersecurity events and the robotics subcommittees. So do you guys wanna vote on who's gonna be part of the subcommittee? Well, we we can't create a subcommittee without that being explicitly set in the agenda.

Oh, okay. That can't be part of the work program, I know? Good to know.

It has to explicitly say form a subcommittee to. Oh, I think we've done No.

Must be on the agenda.

Yeah. We've definitely been following Yeah.

Except for that.

We have without without it being on the agenda. So let's make a note of that.

Of course.

So, basically, we're adding a vote to create a subcommittee. Yep. Alright. So then do we remove the item five?

Item five is sub completely update.

Mhmm.

So the first item is that we had to finalize the date

Yes.

Right, for the cybersecurity event. So we sent out service to the potential panelists Mhmm. As well as to the council members and the city mayor. And the date that's emerging as that's is October 1.

Okay. Okay.

October 1 seems to be permanent for all the panelists as well as the mayor as well.

And what day of the week is October 1?

I believe it's a Thursday. Thursday. So looks like that's I think we'll have to work on that to to finalize that. Right?

Excellent. Guys I don't know if we can even if we can do that.

Yeah. No. We can just finalize. But Thursday is a good day, I think.

Yeah.

End of the week would be easier for people to go.

I just for the information of the panel, I will almost certainly be unavailable that week. Okay. But it'll be the whole week, so don't move anything on my account.

Well, that's the one day that it works for everyone. All of understand. That's the day we need to stick with.

This is not a request, just an FYI.

Okay. And so mayor Killimore has agreed to inaugurate the event as well.

Oh, that's nice.

You know, Amy and so we have lot of panelists, so we need to finalize which how many panelists we need. Last time, we had five including the moderator. Right. I mean

Five right now?

We have, like, seven or eight we? I don't know if everyone will make it. So my thought process is finalized on the on the four. Right? You said we'll have only five last time. I think that was a good amount.

We had five last time. Not including them on not including you.

Not including me. He had five?

Think so. Yeah.

Ramesh, Robert, 5059.

It was four.

It was four. Oh.

Yeah. Including you. Right?

But we Yeah.

Broadened our scope in terms of companies that they all work for this year?

Well, last year, they were broad. It was the first year. We had a couple of from Yeah. Yeah. Follow-up to this.

This was completely You're right. From different sectors.

That's awesome.

Actually, we had five plus you, the Homeland Security guy dropped off in the line.

Correct. Correct. That's true.

Back on.

So he's sharing availability as well.

Yes. If he's So I

think we should bring him there.

Is he still planning to dial in or we'll leave?

No. He'll be present. Yeah.

So in person is more on.

Yeah. So we should bring him in this time. Right? Yes. For sure.

That's a good perspective.

And then I haven't checked with Tripti, but all the other panelists are available. Good. Okay. Awesome. For October 1. And Tommy was going to check with Erin.

He did. And she was available, but not on the first.

And we Yeah.

She was only available the seventh, I think, of the dates. That was Erin West, the one that did it two years back. She works from the she used to she's retired now, but she worked in the DA's office. So she had some really

good She had a very good insight.

I remember.

Best presenter

and just Oh.

And some of the real work cases we talked about. Yeah. Yeah.

Yeah. And things that were eye opening to

Yeah. Yeah.

All of us and and the kids that were there, which was really nice. So so we did talk about bringing that Ria on. Remember Oh, got it. She the experience. She works with kids. I think she is high school or just after high school age. So that might be a good perspective and trying to get more younger, the youth audience to attend.

Right. So Ria, did Madeline of German chair?

She's the one that reached out. She has some cybersecurity momentum or act or some kind of change for citing. She has a movement. Thank you. That's what I was looking for. Okay.

She has a a email from her. Right?

Yes. Yes.

So she's we are checking on her availability.

Okay. Good.

And if possible, we'll bring her in for the next commission. Second meeting. Oh. Perfect. That's the plan.

Oh, can put that on agenda then.

Yeah. Yeah.

We need

I know Marilyn's working on it. Right? Marilyn's working on it. Okay. Yeah. She was gonna come to this one,

but I don't

think it worked out. Okay. So that's the plan right now. So shall we finalize the date as October 1 and inform my

Yes. Yes.

Yes. She was appreciated. Then we can nail down everything else as far as the city goes. Yeah. Video group and all of that.

Yeah. Because last time, we had some issues.

Yeah. Well, we had to change it up.

Because because it's been we were thinking of things in the last minute, and we couldn't make things up. Yeah.

Yeah.

Yeah. It's okay.

That's a a subcommittee report. Okay.

And

the other one, you will start working. Fill up something by next week.

Now is our next meeting scheduled for July 1 or July 8?

It's usually the first Wednesday of the month.

I can make it on the first.

Two months.

If it gets moved in July, I won't be able to attend.

I won't.

July 1.

July 1. So I can get Tommy to fill in, or we can move it. It's up to you guys. It just depends if other people are on vacation that

Yes.

Oh, no. No. No. Wait. July. July 1 is a Thursday.

Yeah.

So, no, it wouldn't be July 1. It would be the seventh, and I'll be Oh, really? Okay. My car is over the next week.

This was July 1 is a Wednesday to me.

July first first is a

Wednesday.

So it would be that week. But that is a holiday week. A lot of people have Yeah.

Congestion. So we have this. We have Yeah. The sixth off as our holiday date and not the third. But there's Sixth off? Yeah. We have the sixth off as our substitute day.

Ours the the third.

I think I also have the same

sixth off.

So does the eighth work for your calendars? We could throw that out there.

It will work for me.

Yeah. The eighth is confirmed.

Okay. We'll I don't know if I'll be able to participate on the eighth because I may be on travel. I'm going to India, but I don't remember the exact date.

If you're in India, can you join remotely?

If I'm in India, that's fine. I can participate remotely. Okay. But if I'm in between transit

Okay. I see.

Then it'll be the same. Yes.

Yeah. For sure.

Okay.

We'll we'll evaluate if the AV even works for the city. Meaning, this room's available, and we can make that work and then get back to you. And in the meantime, you can let us know.

Yeah. I think I should be able

to

currently as it looks I'm traveling on the fourth.

Yeah. I should So eight also meeting. Yeah. Yep. Okay. Should be

Traveling on first. Yeah.

Should be celebrating. Okay.

So it will glad it works for you. K. Staff and commission reports. So do we have to take public comment?

Public comment?

Yes. We do. We have no speakers share.

Okay. It's a good thing. Okay. Stop and commission reports. I can talk in the about the mails meeting. So we have the mails reaching on April 18. And, actually, have you anyone here listened to the mayor's presentation that Katie gave?

At the meeting?

At that meeting?

Not at the meeting. She has this she give the annual city address. Right?

Yes. On the

state of the city.

State city.

Yeah. She went through that once more.

Oh, sure. Okay. Yeah. Yeah.

Okay. But, also, she went deeper into some of the things issues. So one of the things she noted was the property tax is collected by the county. Right? And it goes to the city, meaning it's not collected by city of property. No?

Right. And goes to the county and then gets distributed. Yeah. Goes to the state county.

Okay. Or maybe the county. Yeah. So the Santa Clara County, they have it in a pretty the way it is set up that Pupertino is in a very bad place. Ours is like the property revenue share is like the lowest in Santa Clara Town. So Palo Alto gets 15%, Milpitas gets 12%, Cupertino gets 6%.

Why is that?

She said it was something historic. Like, this was set up sometime back, thirty, forty years back. And

Oh, it's probably been some population of the times or something.

Yeah. Depending on the state of development or something. Like, maybe there's there was nothing there. Maybe it has developed later. Right?

Mhmm. Yeah.

So maybe it has got a bigger sale and and were considered pretty far or pretty developed. So we are, like, 6%, and lot of them are, like, twelve and fifteen percent.

And probably Palo Alto has 15%. Yeah. I'm sure Palo Alto was also developed

in

that time.

Yeah. But somehow, it has ended up. So I was talking to like, all of us were asking, we we need to continue for any time. He says, none of them. It can't be because all the other cities have to agree to it. And because their budget is fixed, if they increase somebody that means they have to lower somebody.

Right.

So that's why it's in a it's going to be brutal to renew membership. But property tax is such a messy number. So if you are getting 6%, somebody is getting 15%. You know, you are not get getting that much money

Right.

To run your city.

Right.

No. But this

is And they say

of what is collected from your city. Yes. Right?

So city have Sorry. We keep 6% of what is We collected by our city?

They collect 10%. 6%.

They

keep ninety four percent of virus?

Yeah.

That's

What about the school district?

So Palo Alto gets 15%, and they keep 85. So why

Why did they have to take part of the percentage from another city if

Yeah. Because because it is our

Pull up my

I thought it is coming from county. So it's between county and the city, not with any other city.

No. There is everybody's represented there too. Everyone. Because the idea of being your budget for

example, the county is $1,000,000. So if they give us back next to 100,000

So the county still wants their fixed budget.

Yeah. Yeah.

But they're saying if I'm going

because from, like, Palo Alto, they're taking 15% from just the funds that come from Palo Alto.

Yeah. No. It's he's no. He said, like, oh, they Oh,

they're giving back.

Like, they give back 15%. Right. They keep 85% of Palo Alto, and they keep 94% of CooperTeam or whatever.

But how is that fair? That doesn't seem

Yeah. It looks like, you know, it's going to be so heavily contested that Pubertyno and Saragavala will not have the votes too.

Well, in the Champlain County right now,

is that

course of action or it was just a FIF? Just FIF.

But there was no, like, we're doing this about the about the No. No.

Thought there was another one that I saw as a public I read in the public was the sheriff's

Contract.

Contract. They sort of increased it. They They've been been renegotiating Yeah. Contract.

That license plate reader, the reason it got canceled is things are the Cloud County could not work out again the existing vendor. So they have to find another vendor.

No. It was because Yeah. It was because that vendor had known to basically Leap data.

Leap data. I see.

Data and and and go against what the policy what they agreed to in the policy. Yeah. And so they want to still allow ALPRs, but they don't wanna allow flock as a vendor because they abuse their

Yeah. Yeah.

Yeah. But this is I

had a whole analysis on flock cameras, actually, on what the issues are. I it to you.

Yes. Yeah.

Yeah. But, yeah, we really need that because crime is, going through my roofs.

Okay. And there's other vendors out there.

Yeah. I think they are talking to them.

Yeah. So we're waiting for the for basically all of the cities to come together and and the county to decide which vendor they wanna go with because it doesn't make sense for us to all select around.

Yeah. Also, this property tax, they just standardized all the same.

Yeah.

But, you know, we do so much better.

Yeah.

Because that'll be a lot more dollars.

I don't know how they Well

they pay I think he has subsidizing others because our property tax is very high. Right?

No. We are not subsidizing. County is getting more money out of us.

Yes. So guarantee is

Yes.