Communication, Technology & Information Systems Committee - Regular Meeting

Good morning, everyone, and welcome to the communication technology and information system. We start committee meeting for 02/04/2026 at 08:30 in the Executive Conference Room. In attendance, Cesar Cardenas. Here. Juan Moreno was now unable to attend, and then Sherry Reardon. I'm here. First of all, we need approval of the minutes from 01/07/2026.

Motion to approve the minutes.

I'll second. All in favor.

Aye.

Aye. Next would be citizens to be heard on agenda items. We don't have any citizens here to be heard on any agenda items. So we're gonna go to a presentation, for the Pellegrin demo by Chris Bolton and the Pellegrin team.

So I'll just start out really quick before we start the demo. Thank you for having us. We really appreciate it. And we're really excited to kinda show you a live demo of this product from Peregrine. And I'll let them introduce themselves when they sit here and and they do the demonstration, and they can kinda talk about their their background and and such and and where they are with the company.

But, like, overall, as I said, kinda in the pre council, this is kinda like an overview of all of our products that we have. So everything is kinda siloed. And and some of the and I have them printed out here, but some of these systems that we have that really don't really talk to each other is our is our record system, our evidence system right now. We're using our video system, management system, our ticketing when it comes to our citations, our adjudication tickets, our crash reports, even our internal fare cases, our use of force cases. All these are siloed systems that don't talk to each other.

And one thing we also of the important ones is time, like, when when you're talking about sick compute or sick time and everything. So none of these systems talk to each other. What Peregrine will allow us to do is not only connect them all together. So if we're, like, say, searching for a person or a vehicle or or or an address or something, it's all linking everything together. And we're able to do a much better search when it comes to that when we're, you know, investigating a crime.

But, again, it also does is there's analytics on the background. Again, I'm not the expert in not say Peregrine is, but where they can do custom stats for us against all this data that we have that we currently cannot do. So when we're sitting there, we have to go before a community meeting or council meeting, you know, especially from a command stand staff standpoint, we will have data at our fingertips that we can pull up pretty much on a moment's notice. And it'll be more much more accurate than we're getting right now. Right now, we have an analyst that does a fantastic job that sits there and and puts our data together.

But that's again, that's one person, and she has to sit there and calculate that by hitting multiple different databases and puts it together and then sends it to us. But there's many times where we get phone calls about, hey. We need this data now. How you know, what's how many crashes are we here are we having at this intersection? Or, you know, what's the crime in this sector or or in this, you know, NLPT area? Or what happened, you know, overnight? Or we have a do we have a string of burglaries going on? We're we're hearing there's a bunch of crime that's happening. We can pull up this the stats really quick for for the department and whoever's asking for it. Instead of sitting here like, hey.

We'll get back to you in maybe a week. You know? And, again, right now, we're relying on one person to do all that for us. And, again, she does a fantastic job, but, you know, she also, you know, has vacation time and stuff like that. And that's we we don't have any other avenue to sit there and pull this information. So this will definitely bring everything together for us. And I know I've spoken to a lot of different aspects of it at BRE Council, and so that's, like, the visual mapping. Like, you know, seeing, like, the visual hotspots. So if we're like, hey. Where's all of our burglaries happening?

Is it Far West? Is it Central? Is it in this particular area? We can sit there and do some analytics and try to figure out, well, is is there things that are linked to it? Can we sit there and now put our officers on on a task force to sit there and address this at these certain times? So we're not really losing, you know, what is really going on with the city. We'd have much more understanding of what what we need to do. I know I spoke on the officer wellness wellness thing. I know they got brought up in the Herald News. Obviously, that is an important part also.

And to be able to integrate all of these calls for service that the officers are doing compared to their abuse or sick time or, you know, even discipline. You know? You can have an officer that has been doing everything they need to do for the past fifteen years, and maybe they've been on some really critical calls, and now you're seeing a pattern where they're maybe calling in sick. Maybe they're having more discipline that they've never had before. And there's some analytics that can sit there and put everything together and start coming up with this early warning system like, hey.

Something's going on with this officer. You know? And right now, all these systems just don't talk to each other. We have an early warning system that's in our current internal affairs, but, again, it's mostly based on just use of force, just, like, crashes or complaints or, you know, shift level counseling, which, again, is useful, but there's other dynamics that are out there that might be more fitting. Even taking time off where, you know, it may not necessarily sick time, hey.

We have an officer that's taking a lot more comp time, more vacation time than they ever had before. What what is going on with with them on that aspect? So there's a lot of analytics that we can use to sit there and definitely help out our officers that might be in crisis that just not aware of at the moment. And before something happens with them or, you maybe it's even a training issue that we're maybe like, hey. You know, something's not going you know, we're we're missing something with this officer. We just need to address it. So, again, that that kinda was a topic. So we definitely see the benefit of this. And and, again, I think we could probably talk hours on this. And I know we're here for a quick demo, but I'll stop talking.

You made me think of two questions, though. Is there any risk of anybody because it's gonna put everything together, is there any risk of somebody not having the authority to have access to some of this information that might come up?

Not having the authority?

Right. You know, not having clearance to see some of it?

Yeah. So depending on the user that or the restrictions that we put in place. So if it's, like, internal fare cases, if you don't have access to it, you won't be able to

see it.

Okay. We can allow you to see it just like we do now with the current systems. We have roles in place. It'd be the same with with Paragran. Okay.

And the other thing, do you do you anticipate this is gonna be helpful with well, I'm not sure you anticipate, but do you, you know, truly think that the open cases that we currently just can't get a handle on this might bring the, you know, the, I don't know, the access you needed to put it all together just like you said with an officer? Absolutely.

Like like looking at old cases

Mhmm.

Kind of where, like, do we miss something?

Yeah.

Absolutely. You can sit there and and take a new look at these cases. Like, am I what lengths did I not look at that might have been part of our other systems? Because, like, our traffic tickets are is a prime example. They're they're very, you know, low key, like, where they're not serious. It's just a citation. Right? But you're getting a person in a car and a vehicle. And a lot of times, if you're sitting there, you're searching for a suspect. You might have a plate, and we're looking through our systems.

But if you don't look into the traffic ticket system and see who may have been driving that car, that might be another person to go talk to. So having these systems altogether does this analytics to where, like, you can really pinpoint who's assigned to like, this car. Could it have been a girlfriend, a brother, a cousin that might have been associated with this car, and another person maybe we've talked to maybe be another lead to sit there and solve a crime. Everything just kinda compounds on the other one to sit there and hopefully get to the point where you have resolution in the case.

Do you have any questions? Yeah. I got a couple more. Yeah, I think, like, the I think I think it's cool how you said it it brings it all together. So would this be, I guess, an example of, like, when we ask for, like, cost for service when we're looking at the liquor licenses and whatnot for a place, does they get a specific does it say, okay. We had a 100 cost for service or 50 cost for but then be able to also say what types of cost for service they were or, like, to say what kind of issues are happening on this place? Because cost for service can mean a lot of different things, right, within that. Would that be something that this can kinda break down?

Absolutely. So it's all tied to our CAD system. Depending on how everything's put into the CAD would be how we categorize it. So we have DISMO codes within our CAD that we will break up. So if it's, like, a liquor violation or something, we'd be able to pull that up. In fact, we'd probably be able to pull that up through the whole city. See, all of our our liquor violations throughout the city for a year, and we do charts that are based on that that are customized. So there's there's a lot of functionality in this, and there's a lot of customization from what I've seen. I know they're gonna talk more on it. But, like,

if the

way I and and, again, they can express a little bit more, but it's like whatever you can almost imagine for the most part as long as have the data in there, you can almost come up with some sort of chart and kinda come with

it. Right.

You know, it's all on the data. You have to you can't it's not gonna make up anything. So, you know, you can't pull anything

out of answer it.

Correct. But what I think this might do also is figure out where we're we're lacking. Maybe we're not tracking certain data that we could be tracking in our record system. Like, you know, would it be great if we could start tracking this? And we might you know, and it might be as simple as having a checkbox within our record system. And now we have another stat that might be very useful that we never thought of before. But I think this might even show that that we might be lacking in some of our data collection.

Another another question I had then and then so I don't know how the you know, I get pulled over and you run my name. Is it just one system that has certain information about me, or is there multiple systems that will now you will have access to, like like, I guess, like, guys so you pull me over, you check me out, you just see, okay, he's got a speedy ticket or a warrant, whatever. It's just one system that says that. Are there other systems that are not gonna tie in to get more information about who it is that you're pulling over or who it is that this person is?

Potentially, but I I don't know if that's gonna be the best case for it. I mean, if we're gonna pull someone over for for a traffic ticket, most likely, we're gonna run for leads. We're just gonna make sure they have a valid license. There's warrants. That's, like, the most important when it comes to pulling someone over. You know, we're not I don't think we're gonna dive deep into their their background. I don't think there's a need to do that on traffic stops unless for some reason there's something hinky and going on with traffic stop and something just seems out out of this.

But there but you could use this system to basically put their name in there real quick just to see if there's who just not that and I'm not I'm using traffic stop as an example, but just in general, if you're looking for someone or whatever, you have that kind it'll bring it all together into one. Right? Correct.

Because we we have the ability to do it right now for the most part. Like but you have to hit multiple different databases, multiple different logins

But this will bring it all together into

one. Correct.

In a

in a much easier format for us to read. Yeah. You know? And and an example too where, say, we did pull someone over and we just wanna see, has this person had more you know, have we pulled this person over and gave him warning traffic tickets before? Yeah. We can pull that up for that for that person and go, hey. This person has been warned, like, three or four times. Right. Right. And, you know, this is, like, their fifth time. And, you

know, you're not gonna get

a warning where you're gonna get a ticket. So, I mean, it could be used in in some aspect like that, but this would probably be more for an investigative type thing, kinda more after the

fact. Yeah. I mean, I like I mean, I think I'll I like where AI is going, right, and and and how everything is, you know, but then it gets into the it can get scary at that when you start to really think about it. Because then I also think about the safety of the officers, right, or the officers' information. Right? Because like you mentioned, being able to tell if an officer is calling off or, you know, because of what they may have may not seen or whatever. Is that information voidable? So then it it it would be used against you guys, or, like, is that, like, are we are we putting you guys at risk by allowing that much data, I guess, being put together in person? Well, there's Or even the officer and or, you know, just the constituent. Right? Yeah.

So, I mean, there's there's certain things when it comes to to Foote. Like, a lot of this and I know they can probably speak more on this, but from from our standpoint, is this is we have the data already. So when it comes to FOIA, we would still go back to the native system for our FOIA request because that's what's more important. This is just basically taking the data and putting it into a much more readable, searchable format for us.

When someone requests to say, I want the that version. I want the pedigree version of the data I'm looking for because, again, now it's gonna paint me a different not say, not gonna paint me a different story. It's gonna give me a clearer picture

Yeah.

Versus just saying, okay. I just want the one piece of information. I want it all at one. So is that something that we are then, again, not putting ourselves to?

Yeah. I know there's there's restrictions when it comes to FOID depending on what is being asked. So there'll probably be certain things. If it's something we we already had generated that we've made, that would be FOIA able. If it's something we have to make Create.

You know?

If someone's asking us for something and we have to create it, that's gonna be different. Gotcha. But anything that is under the FOIA laws that we would have to give up, we will give up. But with redactions in place if needed. And if it's something dealing with someone's, you know you know, sick time or the reason for sick time or things like that, Certain there's things we're not gonna disclose. So they would probably not be be released. But everything would still fall under the four zero one.

Something like that?

I have one more question. Sure. And I meant to ask this the other night. With the the data that's coming together, is it put together and analyzed and, like, in an AI format? Like, where you're you know, the AI has taken over and putting it together and telling

you I can get into that pretty

Okay. Explicit. Okay. So Alright. Well, then let's do our demo.

Yeah. I'll let them introduce

introduce themselves. I'm gonna let Sam introduce himself first. He's my counterpart that's gonna be clicking through the workflows, and then I'll do the narration. But, Sam, go ahead.

Sam Balasano, the account executive here in Illinois. So in layman's terms, just the the sales guy here in Illinois. I've been I live local here in Woodridge, so not too far from you guys. And thank you for having me today.

Glad to have you. Thank you.

My name is Paul Vercota. I'm a public safety executive with Peregrine. I spent a thirty four year career in law enforcement down in South Florida, retired in April 2025 as a major with the Palm Beach County Sheriff's Office. I got first exposed to Peregrine as a customer in the 2023. And my role at the time, I was the major in charge of the Homeland Security Bureau.

So I oversaw our real time crime center, our fusion center, our strategic intelligence division, our threat crime analysis division, tactical intelligence division, the Palm Beach International Airport. So I had my hands in a lot of our operational technology. And I'm gonna give you the caveat that I am not a tech guy. I work for a tech company, but I'm an end user of tech. And, you know, my general understanding is, you know, as an end user.

So I'm not an engineer. I don't get into the, you know, the back end of systems or anything like that. So upon my first exposure to Peregrine, I had never seen anything like it. And I, you know, initially thought, and I'm very skeptical, that this is too good to be true. And then I sat through the demo, realized that they were actually demoing live data in police departments that were customers in other places in The US.

I had never seen a vendor demo use live data before. Generally, it's a canned PowerPoint presentation or something of that sort. So I was initially impressed. It became my my job within the agency to validate and invent the product in the company. I did so, and we ended up moving forward in contracting with Peregrine in February 2024.

So my agency was a customer for a little over a year before I retired and became an employee of Paragrid. So my current role now is I kind of act as a subject matter expert from the law enforcement perspective within the company and act as a translator between police executive staff and sales. So a little quick background on the company. They were founded in 2018 by the cofounders, Nick Noon and Ben Rudolph. Ben Rudolph is a native of Naperville, born and raised.

He linked up with Nick Noon in college when they went to Stanford University out in California. Ben has a computer engineering degree, and Nick has an economics degree. They kind of parted company after college and ended up linking back up in 2018 to form Peregrine. The unique thing with Peregrine is we are not an off the shelf product that, you know, was used in other industries. It was purpose built for law enforcement in a police station in the Bay Area Of California.

It's a US based company headquartered in San Francisco with satellite offices in Washington DC and New York. The company has continued to grow since 2018 to a point where we have about 350 employees now and close to 400 customers worldwide. When I say worldwide, we have customers in Canada, and we are branching off to English speaking countries in Europe. And there's a reason why they have to be English speaking because the way that we use AI in our platform, we have not been able to cross over into other foreign languages yet. Having said that, the company continues to grow.

We have expanded our ability to scale a product to smaller agencies less than 50 officers. We have our first customer that has about 20 officers in the state of Alabama, but we range in size from departments of about 20 members all the way up to LAPD that has just shy of 10,000 and everything in between. So the product is very scalable and works well in those different applications. A quick overview of what we are is we are a data consolidation platform. So we specialize in taking siloed data systems that the agency has control over.

It's their data, but it just lives in all of these separate systems that if a police officer or command staff member wanted to access those systems, they would have to go and log in to each individual system. Nothing is linked. Nothing is talking to each other, and it's very time consuming. When we're able to pull all of those siloed data systems together into one place, we create the ability to kinda give you a single window to go to to pull all of that information together. So it becomes much more time efficient.

Generally speaking, law enforcement agencies are very data rich and very information or intelligence deprived just because the average officer may not even have access to all of these different systems. Not because it would be restricted. It's just too time consuming. And, you know, when they're driving around on the street every day, they can't have their MDT open with 15 different tabs. It's just not practical.

So this pulls everything together into one place to create essentially a Google search bar like you can see on the screen up there. So it's very intuitive for a basic search, and then it can become very complex if needed to do the most intense analytics investigations, networks mapping, whatever needs to be done. We have this ability to pull information together and create the most powerful search that I've seen in any product like this. And that is really the backbone of our system. Because the better quality of search and the return results, the better data you have to to take action upon.

So we can search structured data pretty easily, and there's a lot of other platforms out there that can search structured data. And when I say structured data, I mean, like, RMS information that has a data field, like a last name, first name, address, or anything like that. But in addition to that ability to to powerfully search structured data, we search unstructured data very well. And there is a treasure trove of information and intelligence that lives in unstructured data within a police agency that is generally not accessible. It just lives in a file somewhere that nobody knows about or one person may know about.

Unstructured data is scanned in documents. It could be handwritten forms. It could be, you know, traffic citations or parking citations citations or, you know, old field interview cards or but some of the best examples are CAD narratives, which are generally very difficult to search. Generally, when you search CAD, you can search by an incident number, a location, but the the all of the information that lives in the body of that CAD narrative becomes very difficult to search. We are very effective at searching that, and that's why we get better results.

And where that becomes important is, you know, we we were talking liquor violations before. Not being familiar with Illinois' signal codes and 10 codes, there could be a handful of different ways a liquor violation call could get classified. Or an officer gets dispatched to a a certain type of call and then discovers a liquor violation afterwards. It's listed in the CAD narrative, but it gets coded out as whatever that initial call was. So you miss that information, and you miss the ability to be able to collect it.

We do that very effectively. The other huge benefit of searching unstructured data is body worn camera transcripts. And you can imagine the dialogue that goes on on the street that becomes part of that body worn camera transcript that now becomes searchable, that nobody else in the department may know about it unless they actually watch the video. And there's just not enough time in the day to be able to sit and watch every single video. So we're able to extract bits of information out there to generate leads in a case that wouldn't normally have been discovered or or generated. Yes, sir. Quick just let me let me

have a question. So then if you search a specific incident or time or date or or an issue, could that essentially point you to the body cam footage that you're looking for?

Yes.

I guess.

More or less.

Right? So

Yeah. Because there's there's other links within that body worn camera in the metadata. There be a GPS coordinate or something like that that ties it to a particular search that we're doing. And please ask questions. It is. You know, it it'll be much more interesting if there's some dialogue.

So here here's kind of a quick example that this might come into play is we have a suspect name, and we don't have him in our records. This might be someone that's not from the Joliet, Chicago land area. But maybe we stopped this person either on traffic stop, maybe they're a passenger, maybe with some sort of disturbance or something like that. We get the person's name or something. It's not part of any type of report that we may have. Using Peregrine and putting that that name in there, it might pull up that body cam. You know, from that thing, we can review it, see if that's that person. Now we have a face of that person that might actually be our suspect for whatever we may be looking for. And then we can use that that face to sit there and put it out in the bulletin and go, hey. Do you know who this person is?

Or, you know, or have you seen this person? Or at least gives us that lead to actually actually identify who that person is under their name, date of birth. So, I mean, just kinda thinking outside the box, there's there's so many different roads we can go down on how this thing would be useful, but that would be something like we're using a transcript, you know, where there's some data in there that might not be part of other data that would help us solve crimes.

I mean, I'm thinking about a Google search you can put in, you know, cat toenails when you get you know, like I mean, it's crazy stuff. And I think when you were saying that, if even if it's not written, if it's a transcript and they said the person's name at some point, it would be in there then. Correct?

I can give you a a quick use case. Tuscaloosa, Alabama is a customer repair. They had a violent person's crime that occurred late in the day on a Friday evening, and they had very limited suspect information. They knew the suspect name was Demetrius, and they knew that he used to or currently attends the All Star Academy. The All Star Academy is a charter school for juvenile delinquents and, you know, the criminally impaired, I suppose.

But it's not a county school. It's a private charter school. There was no after hours contact, no way to access those records until Monday morning. So the detective having that limited information, name of Demetrius in All Star Academy, ran a simple search in Peregrine, which returned a result of a body worn camera transcript from an unrelated incident two weeks prior, where they were interviewing a lady in a neighborhood that had called about kids terrorizing the neighborhood. And in the course of that body worn camera transcript, she said, there's this kid, Demetrius, that lives in that house over there.

I think he goes to the All Star Academy, and he's threatening everybody in the neighborhood. So that pointed them to the lady. They went back and reinterviewed her based on, you know, the new crime that had occurred. She pointed him directly to the house. They were able to, you know, establish a perimeter on the house, see who they believe was Demetrius, identify him, secure the house for a search warrant, and solve the crime, and made an arrest that night. That is, like, the

proof need to see the demo. I'm done.

Is the proof in the pudding. And I will tell you, you know, as a career law enforcement officer, that is a capability that we didn't have just a year or two ago. I think it's important to answer your question regarding FOIA. So understand that Peregrine does not generate data. This is data that already exists in the agency in these different native systems or systems of record. What Peregrine does, like the magic behind the scenes, is it pulls all that together and creates the ability to search that data

Right.

That you wouldn't normally have. There is nothing generative, if I said that right, generative about about Peregrine. Paragon. So the AI that we use in the background is non generative AI. It's closed loop AI, meaning we do not share an agency's data with anybody else to try to make the AI smarter.

And that's where you run into problems with, like, chat GPT. You know, chat GPT will actually create information in order to make your argument stronger or, you know, to make its own argument stronger. I I think they called it an AI hallucination. We don't have that. So our AI is completely CJIS compliant, closed loop, and the data is secured, not being shared with anybody else to try to train or make the AI smarter.

As far as a FOIA request, where Peregrine can really help and and reduce person hours and give a better return result is you can run a search in Peregrine to locate responsive records within the agency instead of having to go into potentially 15 or 20 different systems of record in order to conduct those searches. So it is definitely, definitely, you you know, know, an an efficiency improvement in that regard.

Talk about a simple concept that who would thought that all the, as you call them, silos didn't speak? Yeah. You know, I mean, I didn't know that, know, the silos spoke. I I thought it

was You know, traditionally, this law enforcement executives, and I was guilty of it because we all have budget constraints. Right? Law enforcement executives are traditionally guilty of buying just enough technology to make the the job for the average police officer or detective more time consuming and more difficult. This is a platform that fixes all of that. So

This is what we were trying to do for you guys, make it more difficult and time consuming just so you know.

You know, but that increased efficiency becomes a true force multiplier. You know, as a law enforcement executive or retired law enforcement executive, the one thing I learned is we would never be able to hire the amount of amount of manpower that we believe that we need. So in order to work smarter and not harder and become more efficient, technology is really the only thing that can act as a force multiplier. So what it does is it frees up civilian personnel within the agency that are doing analytical work or should be doing analytical work, and it gives them the ability to conduct more rapid searches, get better results, and frees them up to do real analytical police work or investigative work. The same thing for the officers on the street.

Personal case in point, I was a a supervisor of a fugitive task force for many years. And the way that we would start an investigation on a fugitive is we would sit in a circle in a parking lot with everybody with their laptops out. And, you know, you get RMS, you get CAD, you get traffic citations, you get the jail management system, you get gang database. And we'd have to sit there sometime for four or five hours to search and read through all of these different databases to try to generate a lead or find a door to go knock on. That same group that I used to work hand in hand with uses Paragon on a daily basis now, and they get a return result on their search within thirty seconds with an AI summary of all of the information with the bad guy.

So that's where it acts as a force multiplier. One one of the many ways. But we can also, through automations and AI, we can auto generate reports within the agency that used to take analysts days to complete. My old agency had 19 individual patrol districts. It was a fairly large agency.

We had crime analysts in in each one of those districts, and they would have to prepare what was called a crime matrix. They would come in on Monday morning and spend all day Monday and most of the day Tuesday, if they weren't interrupted, to prepare that crime matrix. And it was this the prior seven days of activity within the district to present to the district commander. That's all automated now, and the district commander can look at it on their phone in real time and see everything that's going on. So each one of those 19 different crime analysts are freed up to do real analytical work now.

So, you know, with the the AI automations and the auto generated activity within the platform, you're getting better results in real time, and it becomes actionable in real time. Where, you know, if you're doing a seven day prior crime matrix, by Monday morning or Tuesday afternoon when you get the report done, some of what you're reading in there is ancient history. You can't do anything about it other than, you know, try to pick up the pieces. So it's truly a platform that makes the agency more efficient, and it's better for the community and the victims because it makes the the police officers more responsive to the needs of the community and the victims and get getting better results and hopefully an increase in arrest. So I've talked a lot.

I think it's gonna be important to see it, but I wanna give you the caveat. So in order we are a CJIS compliant platform. Every member of Peregrine is CJIS trained and certified, fingerprinted and backgrounded, and we have access through the SIGIS standards to these different platforms. Unfortunately, I can't show you live data from a police agency, but we do have what we call a demo org within the platform. So it's gonna visualize the same, but it's gonna be AI generated people, and it's gonna it's gonna show limited information.

But it's gonna give you a good snapshot of what the platform looks like, and please ask questions. So without further ado, I'll turn it over to Sam, and he's gonna show you this would be our landing page and what a basic search looks like.

Thanks, Paul. So here's that landing page. Everything's web based, so users at the agency will have a username, password, and to log in to the system. They're directed right here to that Google like search bar. Now as say we're running an investigation and officer investigator detective is looking for a specific person, they can search by an incident number, a case number, a specific vehicle.

Let's just say for this specific investigation, we have a suspect in the name of Mitchell Palmer. Now I can go in here and type in a full name of Mitchell Palmer, but I just wanna for this demo, I just wanna type in Mitchell. And when I click search, when I just search this, single name by Mitchell, you'll see about in this, demo work, we have a 130 different results by just searching the word Mitchell. Now you'll see all these tabs here on the left on this top middle screen here. Now imagine each of these tabs is a different software or an integration that the agency has pulled in.

So we have five people of of having the word Mitchell. We have two different documentations here with arrest on Mitchell. What's really nice here is the Axon body worn camera. In the transcript of this Axon video, the officer said Mitchell. So you see there video transcription with Mitchell highlighted. The investigator could come into here view that video fairly quickly. And, again, that's just a demo video. But you can pull up that Axon video over that direct API connection, and that officer or investigator could view that video.

And let me jump in here real quick. You had asked a good question earlier about permissions or unauthorized access. The platform is permissionable down to the granular level. My old agency had 39 different user profiles within evidence.com, which was Paragon is able to mirror all of those 39 individual profiles to guarantee restricted access to certain cases that are sensitive or body worn camera that's sensitive. Generally speaking, a a line level patrol officer would only have access to body worn camera video that they generated themselves.

They wouldn't be able to see anybody else's. And then the permissions increase as you go up the hierarchy. So a sergeant would be able to see the people on their shift. A lieutenant would be able to see everybody on the night shift and so on. So it's permissionable down to the individual granular level to prevent unauthorized access to insensitive information.

K. That's important. Thanks, Paul.

Next tab, we have so when Paul was talking about that unstructured data. So even in a a case summary or a narrative or different citations, what we're doing in the background as well is it's we're basically OCR ing everything. It's basically looking for kinda just like a license plate, how it's looking for letters and digits. But what it's doing in the background is finding that unstructured data. And when I search Mitchell, if something's in pencil, a sharpie, written citation, it's also looking for that Mitchell, and that's why it's populating there my search when I search that Mitchell.

And OCR is optical character recognition.

Okay. Down

to warrants, use of force reports with the name Mitchell involved, even city parcels, Ezri layer mappings. Mappings. We have incidents, which is, like, calls for service with anything from, like, a Mitchell Road or somebody even a person in Mitchell, but all you see all these different results from just that search that word search by Mitchell. Back to that investigative search, we were looking for our search was for, Mitchell Palmer. It actually is that first person here that you see there.

A few different things we have, you know, quick view like date of birth, sex, race, phone number, residential address, kind of the basics behind, Mitchell Palminger. What you see here also is within the AI inside the platform, it is actually reading through different case narrative summaries, and this is customizable to the agency of what what we call safety tags. So in a in a report or a narrative in in the CADRMS, it's somehow there was gang affiliation involved, and he also was a convict is a convicted felon. So very, very fast on a simple search. We have that, you know, at our fingertips.

Ready to know what Mitchell Palmer is all about. Now if I click into Mitchell Palmer, this is what Peregrine calls a person dossier page. So on the left hand side here is what we call a baseball card view with full name, date of birth, life driver's license, you name it, weight, height, eye color, the basics on Mitchell Palmer. This middle section here is kinda where the magic in Peregrine happens. It's where it's connecting everything that we're bringing into the system with all the different integrations.

So in Mitchell Palmer's case, we have his recent cases. We have his recent arrest. We have any CAD call incidents with with Mitch Mitch Palmer involved, any Axon body worn camera that this person has been involved in, and we could view that right on platform showed. Also, even, like, related person. So, again, if he had gang affiliation, we might maybe we wanna look into Joe Peterson as well.

Maybe he's part of this the same gang or his brother or cousins that related related to him. Same thing as related vehicles. Maybe he's he's not even the owner of the vehicle, but maybe he got pulled over in his sister's car one day and we have another lead to lean on with these related vehicles. There's other associates in cases as well. Possible associates from the same home address as well.

And then what's really, really nice for the officers or investigators that are are looking into Mitchell Palmer here. Just like the other safety flags, it is reading through all those different case summaries, narratives, and giving a very, very quick highlight view of what Mitchell Palmer's about. So you see he's a convicted felon, documented gang member, and his gang moniker is smiles, domestic violence, and so on and so forth. And what's really nice about Peregrine and how we talked about how the AI is not making anything up, always they'll have a direct connection from the original narrative in these it might be a little bit hard to see on the screen there, but you there's always a link to the original narrative to that, and you could kinda base off of why that's why are they coming to that conclusion in that in that full person history search?

Everything is live and linked. So if there's something of interest that you need to go to, you do it right from that page. You click on it, and it either opens up in a new tab or it goes right to it on that page. It's we call it cop proof. So you're not rewriting any of the data backwards into the native system. So there's nothing you can do in the Peregrine platform that's gonna harm your system of record. So if you find yourself down a rabbit hole in in Peregrine that you don't like, you either hit the back button or you close out the new tab that opened, and you're right back to where you started from. And if that doesn't work, you click home, and it's gonna take you right back to the search bar where you started from.

And last thing I wanna show here in that person dossier page, just an example of, like, specific, you know, past case that Mitchell Palmer was involved in. Same thing as that person history. It's also could summarize that case for you in a very good, you know, bullet list. You're not going through pages and pages of documentation. But we also have, you know, the cat call related people that exact acts on body worn camera to that specific call. And again, wrapping everything into one view for a investigator detective to see, hey, past cases and kinda get a summarization of, you know, Mitchell Palmer. Is there any questions with that person dossier search?

One question. Yep. This might be really simple, but so what if you put in Mitch? Yep. And would it just give you a longer list of people? The more specific you could be Absolutely. Okay.

You got it. Yep.

And we can do advanced searches. We can do fuzzy searches. So if the name was Jessica, you could do a fuzzy search because some people spell Jessica with one s, some with two, some with a c, some with a k. When you do that fuzzy search, it's gonna pull up every Jessica in the system.

And what does a fuzzy

search mean? So it's it's

expanding the ability to search instead of just searching Jessica with a c. It's gonna search anything that sounds like Jessica.

Oh, okay. Alright. So

I type in Mitch. Now it's like so it's not like fuzzy, so it also is populating now like Micah because it's very close to when I click that fuzzy. So, again, getting you more results to kinda find that needle in a haystack and Zero research. Yep. Okay.

Thank you.

Yep. So that's just one aspect of Paragon. The next search I'll show you is, like, is what we call, like, our map application. So DC kinda talked about this a little bit earlier, but, like, let's just say, like, we're in we're at a council meeting or, you know, DC and team of Joliet says, you know, there's been a lot of crashes in in town. What's going on? Is it a specific intersection? I know there's been a lot of, you know, reports going on, but where and when are these happening? Very, very quickly, I could go into the system and just say we have all our different data types here. I could click on crash, and I could have a date or date, time, or range. But just for demo purposes, I'm just gonna do all time what's in our demo org here.

And before I click create live layer, there's gonna be 250 different crash reports that populate on this page very, very quickly and have that, you know, situational awareness of kinda where this is even happening inside the town. I could break this information a little bit clearer by going by cluster and kinda seeing and zooming out and kinda seeing, you know, the hot spots of the town, what's going on here. Also, look at display, like, on a heat map as well so you could diff different ways of visualizing that as well. And let's just say, you know, we're looking at this and say, hey. We do see a lot of things happening on this. I believe it's San Pablo Avenue.

It's like the main intersection in town.

Main intersection in town. The San Pablo Avenue. Here it is. And we wanna do a little bit we don't really care about the, you know, the one offs or two offs of, you know, maybe, you know, in inside the outside of the town here. So I can run another search and say, show me things that happened down here on the San Pablo Avenue. So I can pull up another map here.

Where that becomes, you know, critical is, you know, generally speaking, if you're gonna try to conduct enforcement activity, you want to know about crashes that happen on the roadway. What ends up happening is a lot of crashes get lumped into the total number, but they're parking lot crashes. Somebody backed into something in the parking lot. We're never going to be able to prevent that. But if it's people running red lights, if it's people driving recklessly, or people speeding, we wanna know what's happening on the roadway. So we can do that pretty effectively with the search that Sam's gonna show you here, where we can just restrict the return results by drawing a line down San Pablo Avenue and showing us exactly what happened on the road.

And when I when I do that that line kind of search, we have that San Pablo Avenue down here. And what's really nice is it actually can break down the data and what I'm seeing. You see the points on the map, but what does that really mean? So you see, like, multiple different addresses where those crashes happen in specific areas. We could break it down by specific beats.

It looks like there was 14 crashes in beat one, ten in beat beat three, and so on and so forth. You can see dark light conditions if if it's daylight, dusk, dawn, if maybe sun's sun is getting in people's eyes when the sun's going down, we could kinda narrow that as well. And even by, like, officer that went to that crash and kinda or kinda filter it out by the specific officer that's actually going through those crashes. So a lot of the different data and a lot of, like, things that we wouldn't know necessarily, they break it down here on the summary search. Also, what's nice here, it also will break it down as as a heat grid as well.

So we see, like, for an example, looks like three, 04:00 here. There's been four different accidents at this specific time. Why is that? I could click on this fourteen hundred hour, and now here's those four different crashes that happen at fourteen hundred hour. And I could kinda dive in a little bit deeper of when and why.

Just understand that that heat grid looks much less impressive in this demo org because we have a limited amount of data that's that's loaded in there. There's it's only showing 250 crashes. But I can tell you as a former patrol supervisor and trying to dedicate manpower to certain problems, that was information that if you could get it, it would take a week for an analyst to dig through and find all of that to be able to, you know, give you the information on when to deploy and where to deploy. Now it's at your fingertips.

So that's just one example of mapping. Think of, like, again, like, DC was saying, like, maybe there's been a rise in auto theft or commercial burglary, things like that. I just searched crashes, but think of all the different other avenues that you could run that search and mapping and have that resource allocation for DC commands that to say, hey. We might need some more guys on on night shift in the Southwest part of town because of autothusk, you know, rising in that area. So a lot of different examples or use cases you could do with that map search.

What it does is it allows your your data to allow the agency to act more like a speedboat instead of an aircraft carrier. Because when you get that critical information in real time, you're able to respond to it instead of react to something that happened a week later, and that's huge.

The last section I wanna show on Peregrine is the different, I know we talked about it a little bit, but the different types of dashboards that we could create. And I know Paul we're gonna kinda I'll navigate this for Paul and kinda have him talk about what what you're seeing here. And I can make this maybe in a white to make it

So this would be an example of something

See that better?

Yeah. Yeah.

That's much easier. And I'm half blind to begin with, and I'm sitting at the far end of the table. But generally speaking, this is gonna be what command staff is gonna be more interested in. It it's gonna allow them to kinda keep their finger on the pulse of what's important now within the agency. And, sir, you had asked a question about, like, you know, liquor violations or whatnot.

And I understand, like, the flavor of the day can change, you know, from one day to the next. These dashboards are completely customizable. There is no limit on the number of dashboards that you can have. And if this week, it's liquor violations and, you know, next week is traffic complaints and the week after is loud music or loud noise, we can dash board all of that activity. So, you know, if if you're getting an inordinate number of complaints from the public or your constituents and we need to monitor something more carefully, we have the ability to do that in the dashboard.

And if it's something that is not displaying any type of siege's critical information, that dashboard would even be shareable, you know, in an email form, you know, probably not being able to link back to the information, but to just be able to see the numbers, dots on a map, and a bar graph, that would be something that could be shared with the commission.

So that's just one example of crime stats, like, as one example.

Let me jump in there real quick for one more thing too. So some of you may have seen, like, a Comstat presentation at some point in the past. And and generally speaking, a Comstat presentation is using a PowerPoint, you know, using PowerPoint slides. For lack of a better term, they're dummy slides. None of the information is live or linked or anything like that.

We can click presentation mode and, you know, create a dashboard to basically run a Comstadt presentation and have all of the information be live and linked. One of the the downfalls of a Comstadt session is you have an analyst or two sitting in there, and command staff starts asking questions of the data on the screen. And that analyst has to take notes and go back and dig up, you know, more data, and it takes a week to get the answers. We can answer, you know, those questions in real time just by clicking on the screen and pulling up, you know, from the native system, whatever that CAD report was or whatever narrative is in RMS and get the answer right there in real time.

And when he's saying, like, live and linked as well, like so even, like, on this crimes by month category, like, say this week five, we have this 39 property crimes. Because it's not a static PowerPoint, everything's live and linked. When I click on that 39, here's my 39, you know, property crimes in this week five. It's right on my fingertips, and I it's not a static. It's always updating, refreshing. The So things that you really wanna see from a day to day, week to week, month to month basis, it's always constant refreshing and live link and keeping command staff up to date of, you know, real time stats. Absolutely.

And we can make different dashboards for every different division in the agency. You know, if crime persons needs to, you know, track, you know, robberies and shootings and, you know, assaults, we can build a dashboard for that. Crime property can have a burglary and auto theft dashboard. Patrol can run a call for service dashboard and refresh it every twenty four hours and look at everything that's happening citywide or, you know, narrow it down to a particular patrol zone for that requested time frame. Completely customizable and no limit on the number of dashboards you can run.

So so I'm gonna say one quick thing. So when it comes to our, like, our sectors right now, like, getting information from shift to shift is is hard because you don't know exactly exactly what happened from the shift prior or maybe a week prior. Our officers would be able to sit there when they're assigned to their area, say, Sector 20. They'd able to see, hey. What happened before I got in shift? What happened yesterday? What happened during the weekend when I was off? And they can sit there and see what type of calls happened in their area without having to sit there and try to pull up a CAD report, which isn't gonna be that accurate. And so I can be sitting there and laid out in a format that they can read it easily. So they'll be able to sit there and have a much understanding of the areas that they're sitting there patrolling and know where maybe there have been some problems in areas or maybe, hey.

This this house has been having parties late at night or suffer noise complaints. They would have, you know, nobody ahead of time knowing that we've been there before. And they could do that at the beginning of their shift and have a dashboard for it.

We can yeah. We can create an AI generated. We call it a shift pass along

Okay.

Log. So and it refreshes every twenty four hours, but it's gonna show any significant calls, any critical incidents, and there'll be a a box with all of the CAD calls. So you can see a you know, in this particular zone, they ran a 102 calls for service in the last twenty four hours. You could actually click on that one zero two, and it will show you the CAD entry from every one of those calls. But then the AI summary breaks it down into critical incidents, and those are parameters set by the agency, whatever they consider to be a critical incident. And then any cases of note, like an arrest or, you know, any other significant incident, all live and linked right there. So when the patrol officer checks on at the beginning of the shift, they can pull it up and look at it and see what's basically, what's important now, the wind principle. Right?

I just have a question for you, Paula. Yes, You, because you're self proclaimed not an IT tech guy

Right.

How daunting was it for you in the beginning to learn it?

So it's very intuitive because it creates that, you know, Google search bar, and that's human nature nowadays. Right? You know, if you have a question that you don't know the answer to, what is the first thing that everybody does? They pull out their phone and go to Google. Right?

So I I say the statement, it's just too bad we don't have one of those handheld computers in the room, you know. Correct. Joking. We know that we can find an answer in

a There's a mobile app also for Peregrine. It's not gonna display some of the more complex things in a pretty fashion, but it's gonna give you the search function. You're gonna be able to look at dashboards, you know, for command staff if they're sitting in a council meeting or, you know, something like that. But, you know, for a patrol officer or detective out in the field, they can pull out their phone, go right to the mobile app, and run a search, you know, on a name or an address or anything like that and have it hands on in

the field. So you would say it starts with the search and they kinda get sucked in after that to

to No doubt.

Get into it.

And listen, you know, I I started the job in 1991 before we had computers in the cars and before there were cell phones. We were still using pay phones and handwriting reports and everything else. And then when laptops came out, we had the dinosaurs in the administration. Nobody's ever gonna wanna learn how to use a laptop, and now people won't live without it. So after the initial exposure and it was it was a critical point that I brought up about new technology and especially new software applications within an agency because traditionally, it just bogs everything down.

And, you know, patrol officers there's two things that cops in general hate. They hate change, but the only thing that they hate worse than change is the status quo. So, you know

Oh, there you go.

When you introduce something new like this, you know, there's gonna be an initial transition. But we have a team internally that is gonna come on-site and sit with whoever the agency determines to be the power users. And we're gonna look at workflows and the the the current daily challenges that the agency is facing and help improve the processes and the workflows. And then we bring in our training staff behind them, behind the deployment strategist, and we'll do individualized training for different groups within the agency that the department pre identifies, identifies, generally, like a command staff training that'll be hands on, generally, a a detective or investigator and analyst training that'll be hands on, and then we'll do patrol training for as many patrol officers as the agency requests. So, you know, after that initial exposure and that training and people start using it, once the the first success story happens from within the department, people kinda like, oh, okay.

Maybe this isn't that bad. And they start using it and,

know you Nothing else everybody knows how to search. So No doubt. You're starting there and you're gonna

No doubt. You won't have everybody building a dashboard. No. You know, it's just it's not practical. Right? But as far as the search function, the map, the map is pretty intuitive and fairly easy to use. And when you start to dive deeper into a search and you look at the networks and everything, you know, if you if you run into, you know, a criminal case and, you know, you think the person may be a serial burglar, you know, you start looking, oh, yeah. This guy's he's been stopped in this car. And, hey, I remember hearing that description of that car in a neighborhood where we had a burglary a week ago or something like that. You know, for the the the more self initiated type officers, this is, like, a gift from from above. Yeah. So

I from our standpoint, I I don't think we're gonna have a lot of pushback on this. I mean, we we did a demo already with a bunch of people from different aspects of the department already. And when they walked away from the demo, and, again, it was, like, about an hour or so demo, they were already sold on it. And they've been asking me, hey. When are we getting Paragrid? When are we getting

it? Yeah.

And, again, you know, it's it's just that that force multiplier with their their daily jobs. So I think once we implement this, you know, them sitting there and, you know, adopting is gonna be very quick. I I don't think we're gonna really get much pushback at all if any. You know, I think it's, one of those things when they first start using it and they actually see what they can do, they're pretty much gonna be sold out.

Yeah. I think so too. Yeah. Alright. Was there anything else that you'd like?

Just a cup. I know, like, just a couple more other examples for, like, just, like, in even internally now, like, times were from, like, priority one to all the way to priority five and see those average response times. Again, just not even, like, index crimes that's outside of, like, the department itself, but what's going on internally just, like, for response times, we could build these dashboards out. And I know, like, officer wellness is a huge huge main focus as well where, like, this is the officers. For another example, like, another agency out in California, they're kinda using this dashboard as well, kinda assigning different types of cases, calls are going to crashes, people that things that they're dealing with and have, a point system to them.

So as a command staff, you could react to these things, you know, pretty quickly of, hey. Officer Arbor here is, you know, leading the point system. What kind of calls is this officer going on? See all those different things, and then maybe call them and, hey. How's everything going? You need some time off? You I saw you went to a a pretty critical call. Is everything okay? And kinda keep up with, you know, your your officers, your detectives, investigators inside the department.

And, you know, what we hope to do here, you know, you've heard the cliche, you know, connect the dots. Sadly enough, oftentimes, when something bad happens, you know, the the response after the fact is, oh, wow. You know, all of the information was there. You know, all of the dots were there. You know, We just weren't able to connect the dots in time.

This is a platform that allows you to connect the dots because it puts it all right there in front of you. You know? In a live dashboard like that, you're gonna be able to see exactly what your officers are exposed to on a daily basis from a wellness standpoint. And if somebody is way out of the the range of what would be considered, you know, normal or healthy, it gives the agency an opportunity to respond to that before it's too late. And especially, you know, the deputy chief mentioned if somebody starts taking more time than they usually you know, more sick time or more leave time or, you know, somebody's, you know, citizen complaints spike or they start using force more frequently, you know, you go right back to this dashboard and you say, okay. That immediately allows you to connect the dots and we can respond to it.

Yeah. And

that is pretty much what we wanted to show today at Peregrine. Is there any other questions?

Well, I'm gonna learn to say your name correctly. I mean, mean, I could say Paul and Sam. But, you know It's you need. Peregrine. Do know

what Peregrine is? And I'll give you, I should've in the intro.

I will. I listened to the the the two creators' last names. I'm like, couldn't they have used one of those names? Yeah.

So peregrine, it's a falcon, and it's the fastest animal on earth.

Oh, okay. Well, there you go.

Apparently, at a dive speed, it's over a 100 miles an hour.

Wow. So Well, it makes sense.

Yeah. Cool. Alright.

Well, I appreciate you guys being here. Thank so much, and I'm excited about it. I wanna play with it.

Impressive. I I have one caveat to this. This whole thing and and I'm not trying to put a wrench in this whole thing. This is something that we're currently working on. I just wanna you know, just for being transparent about where we're at on certain things. This is contingent on getting our CAD data from Will County 911. Oh. And me and Chris have been working on this for the better part of, like, a year and a half of trying to get our CAD data into for our our record system for Axon. And we've gone through many hurdles, hurdles, and and it's it's getting getting to to a a point point where where we're we're gonna gonna sit there and and probably do more because we're not we have a meeting this Thursday on it. I'm hoping to hear more updates, more positive things on it.

But if we don't, we're gonna sit there and meet and and rely on the council members and maybe the mayor to sit there and push us along. So we need our CAD data, our calls for service. Because right now, everything's through the Wilkinson nine one system. Right? We don't own that. We don't control it. It's done by state statute. And in order for this to actually get an accurate data, we need that data integrated into the system. And, obviously, we have multiple systems right now that we've been waiting on to be on the back burner to get this data, and we've waiting for mostly about a year and a half on it. And, we can't even fully use this until we get that data.

And I'm really hoping that we get this data sooner than later so we can fully implement this system, you know, once we get this up and running. And, again, one the things that we're holding off is our is our record system. So right now, we're on a consolidated record system within the county. We're leaving that. We're going to access record system.

It's a much better system to work better, integrates with what we got going on. And one of the holdups that we should have been live with it already, we've been pushed off till this fall. We might be pushed off into 2027 now if we don't get this integration done. And we have sat there and talked to Will County nine one about ways they can sit there and give us access and and pretty easily, you know, solutions to do this. And they seem to be stuck on one solution that that's not even available to us right now, which is, again, we're waiting about a year and a half now for it.

And, again, it's whether it's Axon, we have a a system with our field training software. So we can send and integrate the the cat calls into that. Again, this is another system that, obviously, will be beneficial to have all of our calls or service and our record system in this, but we're kinda being held back because of this lack of integration. So I just wanna throw that out there just so and say we we go with this. This gets approved, and you guys are asking looking for stats within a couple months. You know, if we don't have it, that might be a reason why we don't. It's not that we can't do it. It's that we're sitting there trying to to work with what kind of number one to get our data. And I know we're not the only agency. I know the sheriff's department's doing the same thing right now, trying to get their their CAD data

also. Okay.

So just I just wanna throw it out there just so, you know, being transparent. You know, I I feel very, very confident we're gonna get our data. It's just when are we gonna get it? So I'm very excited about this program. I think it's gonna help us out immensely down the road. I think I mean, you can see we can spend hours on this just going down a rabbit hole. But I just wanna make you know, so you guys are understanding, this isn't gonna be from that aspect. We can still integrate all these other systems. We'll have those readily available. And I'm hoping that maybe this will just kinda come online and we don't really have a delay. But if there is a delay, just wanna be upfront.

We would pull you into a meeting with the city manager and Yeah. Mayor and I'll be there and Chris if he'd like to be there. Yeah. We that's ridiculous.

Yeah. I I agree. Yeah.

Okay. We'll get done. Alright. Do you guys wanna head out? You can. You know, you can stay. But there's a lot of excitement going on. Thank you. Very nice

to you.

Thank you. Thank you. Chris.

Thank you. Appreciate it.

Thank you, sir. It was a pleasure.

You wanna get together?

Yeah. We'll be

to chat.

Alright. We'll continue on to agenda item one ninety four eighty two. Award of contract to ISRI. Is that ISRI?

ISRI. ISRI or e s r I. Okay. Go by it.

I know it's enterprise license. This is however they say it, but agreement in the amount of 30 $361,626.

Okay. So Esri is our GIS software. It's all of our mapping software and all integrations. The city has used Esri for over twenty years at this point. It's you know, they're they're the Microsoft of the mapping world. Okay. The EA agreement covers all of your your standard user licensing, our server licensing, our online integration. So the Ezri products are kind of interesting. They're we use a a hybrid model. So we have servers here, like physical servers here that run certain components, but then we also have cloud based servers.

And that's how we distribute mapping to the public, to our field workers, and things like that. We take that information comes from our servers, kinda gets piped up into the cloud, and then disseminated from there. So the this cost here covers all of that. It's also all of our analytics tools for which is used by pretty much every department in the city uses GIS in some Yeah. Capacity, public works, public utilities for water and streets.

But then the PD uses it with their crime analysts, kind of like these kind of products we were just demoing. Their crime analyst uses Esri products on a daily basis to create all their crime maps and things of that nature. So it's just a kind of woven into the fabric of what we do here. This is just another renewal of our three year agreement.

And I know I noticed it's a three year agreement. Are are is it a renew every year kind of thing, or are we committing to three years?

We're committing to three years. We are but we only we pay once a year. Okay. So we will have an annual payment every year.

Alright. Yeah.

Alright. Any questions? Do mind making a motion?

Motion to approve.

A second. All in favor? Aye. Okay. 9492, award a contract to CDWG for core network switch replacement in the amount of $62,953.12.

Okay. So this is I'm gonna give you the very high level version of switching throughout the city. So we have primarily two different types of switches. We have our core switches, which we're looking to replace here, and then we have edge switches, which are out in remote facilities. So your core switches literally own, like, all traffic for the city flows back through these.

The switches we currently have in the core are about eight years old. So they're just simply reaching end of life. The interesting thing about network equipment is it tends to last a very long time. So these switches will actually be repurposed and we will put them out on the edge because there'll be other facilities that can make use of them. These are like 48 port switches.

They get kind of paired up in our server room, But we'll break those down and we'll put them in other places so we'll get we'll eke some more life out of these. We we always do switches. We kind of run until the very bitter end for them. But they're they're hitting that they're getting to the point where they're not going they're that the reliability is gonna start failing. We don't we don't want that as our core because everything has to flow through them. So this is a pretty standard. We we knew about this. It's been budgeted for. We kind of anticipated playing this all out last year to get this done this year.

Yeah. So

I'm familiar with them. I I mean, even at my small scale office, when your switch goes, nothing works. Yep.

Everything shuts

off. I'm I'm reading this. I'm like, oh, yeah. We're replacing that. So anyways, do you have questions?

Question? Nope. Motion to approve.

A second. All in favor? Aye. Aye. K. 9493, award of contract to Heartland Business Systems for the am I like can I not read? Titanic server replacement project in the amount of $223,922.42.

Very similar to switching. This is kind of something we plan out. So pretty much where we've gotten into the cycle of every other year, we have to do some kind of server upgrade. This is always we are we roll off the oldest server nodes. So if you were to look at the actual server rack, there's a significant number of nodes in there. This one in particular is kind of exciting for us. I mean, totally geeking out on it. Right? Is the nodes we're finally getting rid of are the very last of our spinning disk. So the very old style hard drives and everything will be a flash going forward.

This lets us finally remove the old spinning disk nodes. We'll put flash nodes in. It increases the speed or and overall performance of the system. This is another piece of equipment. We we run these things until you're fully out of support. Like, the the nodes we're getting rid of, Nutanix no longer supports them. So they go end of life. These go end of life in about three months. So we're kind of at that point of we need to replace them. We plan for this. This is, you know, as part of our capital funding. It's already in the budget.

Okay. Any questions? Motion to approve.

Second. All in favor? Aye. Alright. So older new business, I think we've covered that today. Public comment, there is no public. So, motion to adjourn. Motion to adjourn. Second. All in favor? Aye.