On Part 3 of our Data Insights series with Sam Wells, Neighborhood Stabilization Coordinator for Albany, NY & Andrew Kieve, Tolemi Co-founder, we explore Albany’s use of Tolemi for data-driven insights with data visualization, sharing, reporting all in one platform.
In this episode, I have the pleasure of chatting with Sam Wells from Albany, New York, to learn about the work they're doing to make better use of their data in-house and to work more collaboratively across departments. The co-founder of Tolemi joins us as well and together we'll learn what made Albany choose Tolemi to help break down their data silos and unlock the power of their data for better decision-making and what you should know as well in your search for an appropriate vendor.
More info:
Featured government: Albany, NY
Government Guest: Sam Wells, Neighborhood Stabilization Coordinator
Featured Maker: Tolemi
Maker Guest: Andrew Kieve, Co-founder
Visit govlaunch.com for more stories and examples of local government innovation.
Lindsay: (00:05)
Welcome to the Govlaunch podcast. Govlaunch is the Wiki for local government innovation and on this short series, we're talking all about data-driven insights. I'll be highlighting from the innovators in local government leveraging available tools to better use various data sources to make sense of their data in house and ultimately lead more efficient and resilient organizations. Our goal is to expose more local governments of all sizes to the tools available and to provide useful information about some of the leading products out there. Hopefully you can spend a little bit less time researching products and asking the hard questions and get to making smarter more data-driven decisions, much faster. I'm Lindsay Pica-Alfano, co-founder of Govlaunch and your host. Today, I have the pleasure of chatting with Sam Wells from Albany, New York, to learn about the work they're doing to make better use of their data in house, and to work more collaboratively across departments. The co-founder of Tolemi joins us as well and together we'll learn what made Albany choose Tolemi to help break down their data silos and unlock the power of their data for better decision-making...and what you should know as well in your search for an appropriate vendor.
Lindsay: (01:16)
So thank you both for joining me today. Can you each quickly introduce yourselves and share a bit about your roles? Sam, I'll start with you.
Sam: (01:23)
Sure. My name is Sam Wells. I'm the neighborhood stabilization coordinator for the city of Albany New York. My primary responsibility is leading and coordinating the fight against vacant buildings and blight throughout the city.
Andrew: (01:36)
I'm Andrew Kieve. I'm the co-founder and CEO of Tolemi.
Lindsay: (01:40)
Fantastic. Well, to begin, I want to start with a little background on Albany, New York. Can you share with us when this shift began to be more data-driven and how Albany was managing your data In-house prior to working with Tolemi?
Sam: (01:54)
Sure. Our shift to being more data-driven really began middle of the 2010s around 20 15, 16, 17. I started working for the city of Albany in 2017. And as I said, my primary responsibility is leading and coordinating the fight against blight and vacant buildings. When I joined the city of Albany, our data on blight and vacant buildings was just not very good. Each department had its own list of vacant buildings. Each department had its own list of problem properties, and they didn't really talk to each other. Those lists weren't really comparable in some instances. So joining those lists together and getting them all in one central location, where to cross reference them with other data sets and really start to build out more of a data-driven proactive response to these buildings was our number one priority before working with Tolemi we were struggling with that.
Lindsay: (02:46)
Yeah, sometimes the hardest piece is just to break down those departmental silos and get the data in a format that you can share it across different departments. So for local governments, just beginning this journey to down the silos and work toward a more data-driven decision-making can you provide an example or two of the benefits you've realized, um, just from the more holistic data work underway in Albany?
Sam: (03:11)
Yeah, absolutely. Uh, the two real big benefits, meaning sort of grouped them into two categories. You become more proactive as a city in dealing with your issues and you also become more collaborative. And a couple of examples we'll start with the proactive stuff. Like I was saying, we didn't have a good list of vacant buildings. We were pretty good at tracking which ones would come off of our list, but finding, you know, new vacant buildings because that number is never static. There's always buildings coming off the list and then buildings coming on and finding the ones that were, should have been on the list, um, was a struggle for us. And so using different departments data to identify other vacant properties. Um, a good example is water usage from the water department. Zero water reads are a huge indicator of a potential vacant property, especially when you've got multiple of those loads zero water reads at a property.
Sam: (04:01)
The property may look pristine, you know, wouldn't necessarily attract your attention if you're walking around the block. But if you know, it's using zero water and you start to search more information on the owner, and then all of a sudden you find the obituary, you know, you've got a potential problem on your hands with that property. Um, and so it really starts the clock earlier for us in our processes for vacant properties. So becoming more proactive with that data and with the data sharing was really helpful there, we've also used this data to identify unregistered rental properties as well. We have a rental dwelling registry here in the city of Albany, any landlord who rents out, um, units that somebody other than their immediate family has to register them with the city and get them inspected. We can use data for example, from our police department to identify properties that are unregistered and needs to be registered. Right?
Sam: (04:52)
Our police department responds to calls here in Albany that are often labeled as landlord tenant trouble calls for the police response. And the landlord and tenant are having an argument that for some reason requires the police to be called. You know, those are calls we can, cross-reference the addresses with our rental dwelling registry and check to make sure that property is registered. Cause that's a pretty clear sign that this is a rental property and there's working across these data silos, um, really helps agencies sort of look at each other's data, even if it's not that good that's okay. Right. You still need to get a sense of what your partners in the city, what your fellow coworkers are working on and doing. And you're looking at it from a perspective yet to look at it from a perspective of helping each other out, right? So those landlord tenant calls, you know, we're trying to help the police department out by reducing their workload because those are calls that maybe the police department doesn't need to respond to. You know, they might not be the appropriate agency in that situation, but they got called their code enforcement might be the more appropriate agency or department or respond to that situation depending on the circumstances there. So the collaboration really sort of follows the proactiveness and in looking at each other's data, they go hand in hand pretty, pretty easily.
Lindsay: (06:10)
Right. Well you've been partnered with Tolemi since about 2017 using their flagship product called building blocks. I want to talk about some of the departments using this tool specifically the building blocks tool.
Sam: (06:24)
Yeah. So the primary department right now using these tools is the code enforcement buildings and code enforcement right now. And we're using that primarily, like I said, to get a better sense and handle and be more proactive on vacant properties and unregistered rental properties. But, you know, we're also using it to, um, fight blight in general. Our codes department uses this for zombie properties as well. They're looking to identify, um, bank owned or bank foreclosed, vacant properties as the owners left. We're also using it to help assist our community development operations too. And our community development department, particularly right now, you know, a lot of folks are really worried about rental payments, landlord, tenant relationships. Um, and we've been able to utilize this to help target marketing for rental assistance for foreclosure prevention, for community development grants that were, um, out there trying to implement.
Sam: (07:19)
We've used the data in here to target about 900 or so landlords that should be receiving letters from the city, advising them of, you know, available rental assistance, available foreclosure prevention and community development grants to help them with what we suspect is likely a lot of deferred maintenance by landlords who aren't receiving the rental incomes that they have normally come to expect and have had to make cutbacks in other areas such as property maintenance. And then this stuff is always expanding. We have a number of departments that use this product from planning to the police department, the water department, our department of general services, the mayor's office. We're always looking to expand that we're currently working with our assessor's office and told me to help improve the grievance period and the grievance process. We think that can be done better currently, the way it's done involves a lot of paper and a lot of spreadsheets. Um, and it's not necessarily the most time efficient way to do that. So we're always looking to expand.
Lindsay: (08:19)
That's great. And it sounds like a real, super flexible product. Andrew, I want to hop over to you. We'd love for you to explain a bit more about your company and your building block solution you offer to local government specifically.
Andrew: (08:31)
Sure. Yeah. Thanks Lindsay. We're a civic technology company, uh, working in about a hundred cities, towns and counties across the country and really focused on building data integration and insights platform that helps local governments harness the power of all their data and break down those departmental silos that Sam talked about. We were founded on the heels, uh, really of the 2008 foreclosure crisis as so many communities were battling vacant, financially distressed underwater and blighted properties and just generally rising disinvestment and a bunch of the hardest hit communities across the country. And we looked at how cities like Detroit and Baltimore and even New Orleans post Katrina, where the scale of this problem was so large that they had to find a smarter way than just playing whack-a-mole. And so initiatives like motor city mapping in Detroit and code maps in Baltimore and blight status in New Orleans, really where data was foundational to allowing these cities to formulate a strategy.
Andrew: (09:27)
And we also looked at thought leaders in this space, like the center for community progress, which really promotes the need to break down these data silos to effectively address substandard properties, which obviously have a tremendous and outsized impact on the hardest hit communities in the country. And we really recognized that local governments needed to, as Sam described one prioritize where they were focusing these limited resources and then to really start to assume a more proactive stance towards property compliance and housing stability. And we thought that we could build a solution that was scalable and affordable to cities of all sizes, right philanthropy. And we were really looking to build a scalable solution that any community could really play and building blocks is our answer to that. It's a platform that integrates with any system that any department is using across the city or even partner agencies and accounts or counties to track data.
Andrew: (10:17)
So think, you know, property assessment, ownership, tax collection, code violations, building permits, police, fire calls, uh, foreclosures, even utility usage, and off basically anything that the city has tracked in a digital format. We have connectors that we can basically automate that process of pulling the data out of these source systems. It doesn't matter if these are legacy systems, you know, cobalt databases as 400, uh, or, or modern cloud hosted systems. We pull the data out, clean it, standardize it and join it at the parcel level. And then we give our users in the city and easy to use, uh, insights engine and really just a one-stop repository for all that property, data and associated records.
Lindsay: (10:57)
I want to get into the, well, you said you helped clean the data. This is huge for local government. So I want to just clarify and really make it obvious what Tolemi is delivering here because so many departments struggle with collecting the same data, but it's being collected in slightly different ways. And for anybody who's tried to ever massage data that doesn't work very well when you're trying to get some analytics and dashboards off of these databases. So can you go into some of the cleanup that told me helps with
Andrew: (11:27)
Yeah, absolutely. I think this is where it really helps that, you know, we are so focused in our soul segment. Our customer base is local government. So I think we have a pretty unique understanding of some of the challenges of, of integrating this data. Um, and so to assist us in that process, we actually have a, have a home built, uh, spatially enabled ETL tool. So it would extract transform load tool. Um, that enables us to overcome a lot of challenges that we see in this local government, uh, data in, in short, if there is sort of an issue with data cleanliness, if there's an issue with data and compatibility, we'd likely have come across it in one of our integrations. And we basically built in the capacity in our internal tools and processes help to, as you said, massage the data and to clean it.
Andrew: (12:13)
And, and because our system basically automates the process and it's really important to us to keep the data flowing in and up to date, we have a whole series of diagnostics that we run on every single record that we ingest into our, into our system and into our database to allow us to flag potential issues at the source when they happen. So oftentimes knowing this is something we sort of wear as a badge of honor, we're actually telling our partners in local government when they have an issue with one of their services or with some of their data, uh, we're actually able to flag it because our tools are catching it. Um, because we're running these processes on a nightly basis. And as you know, we, we always run into local governments that say, yeah, but you've never seen data as messy as ours now is a sort of people.
Andrew: (12:54)
I mean, that's a field that every local government that we work with has, is, you know, look, we've got folks in our team who are not, we're just not using the tools that we've set up or we've got these legacy systems or where we transitioned or updated to a new version of a system of record. And so we've got sort of crosswalk issues. Uh, and I think one of the things we pride ourselves in is our ability to help not just ingesting the data as our local governments have it, but actually help them think about how to get their data house in order.
Lindsay: (13:22)
Yes, that's fantastic. Well your product suite consists of some other great tools that benefit anybody from a clerk to those in it, code enforcement planning, et cetera. Can you briefly talk about some of the other products just to get a better idea of what a partnership with Tolemi could potentially look like?
Andrew: (13:41)
Sure. Yeah. I mean, I'll, I'll start with just within the building blocks product itself. It is more than just data integration, right. And a front end tool. There's also the ability to do more advanced data modeling that we have some predictive models that we've rolled out and trained across the country on things, as I mentioned, one of them on things like vacancy or foreclosure risk, um, we also bring to bear of supplemental data. So this is not just about unifying, uh, local government's data, but then we bolster that data with, with national datasets on, they can see coming from the United States, postal service pre-foreclosures and foreclosure filings, um, and then overlays like historic redlining to help cities apply an equity lens to what they're doing and American community survey data on really critical socio-economic demographic data. So that's all within the building blocks tool. And then some additional products that we have in our portfolio, publicity is a public facing portal, uh, to allow for data transparency, but also property listings.
Andrew: (14:37)
So think like a Zillow for public property. So working closely with land banks, uh, redevelopment agencies, uh, city, real estate departments. We also have a mobile application, Iris, uh, which not only pulls data from the building blocks platform, uh, but also can, it's a mobile survey application. So folks in the field can actually pull parcel specific data. And then we're really excited about some of the developments and some of the, um, investments we put into slate, which is our first real foray into, into workflow and asset management. Um, as I said, specifically, focused on these relevant agencies, land banks manage their real property portfolios throughout the entire life cycle from acquisition maintenance, disposition, and even compliance.
Lindsay: (15:23)
Wow. Yeah. I was going to ask about some other examples of how local governments are leveraging your suite of products, but it seems pretty clear. So we might be able to skip that one and move on, unless you had a specific example you wanted to share and you're outside of what Albany is working on.
Andrew: (15:40)
Well, yeah, I mean, I, you know, it says that the registry compliance stuff is, is sort of right in our sweet spot because, you know, obviously there's, the return on investment of that is, is, is pretty clear as, as Sam described, um, you know, it, it really, the sort of most basic use cases, uh, Sam described, we sort of call it situational awareness, just knowing everything about a property up-to-date records in a single place. And that has applicability from everyone from a code enforcement officer, responding to a call. You know, I want to know if the police had been out there, uh, tell me if there's been a structure fire and no permit pulled for a year, all the way up to the mayor's office, responding to a constituent complaint and being able to immediately see that her apartments are, are on top of it.
Andrew: (16:20)
The other sort of very common use case for us is really around problem properties and, and problem property owners are slumlords is that as they're sometimes called, we've got an owner match matching algorithm that enables our users to actually link together related LLCs and property owners using ties like mailing address, similar name and even utility billing address. And this really allows city attorneys, housing court officials in places that range from, you know, Spokane to Dallas, all the way to, to Newburgh, which is just south of Albany is a smaller community population of about 30,000 using this tool to make a case against their, their worst property owners. And then the more advanced sort of use cases, um, sort of more advanced models of what I call strategic code enforcement. So in a place like new Orleans, uh, they've got an overwhelming number of tall grass and weeds cases to mow just owing to the environment that down there.
Andrew: (17:10)
And I wanted to be more strategic about, uh, where they were proactive about cleaning lots. So they're looking at data on crime and owner occupancy and building permits, and this is all parcel specific data, even where the city is spending their community development grants and public works dollars. And this feeds a decision support tool. That's helping them prioritize where they focus these lot of Bateman resources. So they're turning code enforcement into a tool to revitalize neighborhoods, support city investments, even lower crime, instead of just sort of running a backlog year after year and sort of responding to complaints as they come in.
Lindsay: (17:43)
And Andrew, other than the work that you guys do to sanitize the data, which again is huge, what you say are your differentiators in the market?
Andrew: (17:51)
Uh, obviously, you know, our, our ETL capabilities and our, our sort of knowledge of government systems and the fact that we've got at this point about 300 out of the box connectors that basically just plug into a lot of the existing solutions that are out there that governments are using to manage the data. I think that the data modeling component of what we do is really unique. Our whole mission is to help communities be more proactive when you have this great stew of data, it opens up a ton of potential for machine learning and predictive modeling. And so we have a number of proprietaries, uh, models that we can deploy on behalf of our cities, do things like identify, uh, existing vacant, or potentially vacant properties. Um, and those models, because they're, they're trained on sort of a national data set, but then honed locally.
Andrew: (18:34)
They're really unique to us and quite frankly enable us to go the sole source route in most of our partner cities. Um, but I, I P probably more importantly than sort of some of our unique, uh, trade secrets. Um, the fact that we look at ourselves as more than just plug and play software. We recognize that as, as you mentioned at the outset Lindsey, you know, that sort of this era of data-driven government is really sort of just gaining momentum today. Um, and so we recognize that there's a need not just to deploy, to give cities back their data and to give them some tools and insights, but also we invest heavily in building the capacity of our partners in local government. And so that means, you know, looking at ourselves as sort of the nexus point of some of these best practices in terms of using data to really catalyze community redevelopment.
Andrew: (19:29)
And so we lean heavily on folks like Sam and the team at Albany, look at the innovative things they're doing and try to disperse that out to our network of other communities. Um, because a lot of the problems are the same. A lot of the capacity constraints are the same, and this is not just software that we deploy really look at, um, building the capacity of our partners in local government. Um, and in order to do that, we sort of learned a few things along the way. Uh, one of those is that for us implementation, uh, really never ends, um, it as sort of cities grow their capacity and have more of an appetite for data, and also have some of the harder conversations with some of their, um, uh, some of these departments that have traditionally been sort of silent in themselves as folks understand the value in sharing data and bringing it together, we can sort of stand up those connections to new data sets.
Andrew: (20:19)
So every single city we have, they grow their data for footprint on an ongoing basis. And I think that that's pretty unique. Most vendors in the software space will charge a hefty implementation fee that implementation fee, you know, we will run longer than expected, but then once that that's over any sort of tweaks to the system will cost the city dearly. That's not our approach. Our approach is that, you know, we generally believe that the more data we have flowing through our platform, the more value we can deliver to the cities and the stickier it is. And so we, as I say, we look at implementation is going into perpetuity as long as we're partnering with government. And I think that's a, that's a pretty unique perspective.
Lindsay: (20:57)
Yeah, definitely. And you mentioned, you know, the problems that local governments are facing are pretty universal, and that is, that's why we created Govlaunch too, to get this type of information sharing and these resources available to go governments at a global scale because, um, you know, Albany is struggling with the same issue that Baltimore is struggling with. And this carries over outside of the United States as well. You mentioned Sam that Tolemi has really helped you guys be more proactive in Albany. Um, so I love any technology that's going to help you as a local government get on the office. Um, so you have the answers before you have issues, you know, hitting you, I'm hitting you over the head. Um, it sounds too good to be true for some of our listeners. So I'd love to get into the onboarding process. Um, as Andrew mentioned implementation, I want to talk about what that looked like from your perspective, um, since you've been with them from the get-go in terms of timing to deploy training of your staff, et cetera.
Sam: (22:00)
Yeah. Like, you know what Andrew really said, a big piece of what was especially helpful is, you know, they're not just taking our data, they're helping not only to clean it and organizing it, but also sharing practices of what other cities are doing with that exact same data. Right. So when they first, when we were first introduced to the product, um, I think if I remember correctly, Tolemi came in, um, and showed us another similar city to ours, um, and all their data in, in, um, building blocks and went through some of the use cases, uh, some of the examples that other cities, how they were using that data, um, which has really illustrated for us, um, and they talked about, you know, what those data sources were. And we quickly realized we have the same data sources, um, that every other, you know, all these other cities do, we can do this too.
Sam: (22:47)
Um, and the nice thing was about Tolemi was that, um, and this is true of many cities, especially upstate New York, smaller mid-sized communities. You know, we have a lot of legacy data systems and every department, um, our data is in all kinds of shapes and forms and sizes. Um, and so, you know, from the outset, we were initially skeptical that somebody could come in and take all these different file formats, all these different, um, data sets and put them on one. But Tolemi was able to work with every single dataset, clean it, help organize it, um, really helped to help us to identify the other uses that were out there. The other, um, unforeseen advantages to combining all these data sets into, into one place. And that's really an ongoing process it's never stopping, and it shouldn't for any city, right? Your data is going to change over your over time.
Sam: (23:40)
Your data capabilities are going to change over time, the strategies and the issues, or the issues that you have in the strategies you need to employ change to, um, a need to change with that. Cities are living, breathing organisms, and our data needs to keep up and reflect that. Um, you know, and then when it came to our staff, you know, Tolemi's always been willing to sit down and walk staff members through how to use the program. They've got very helpful online tutorials, training tools, um, as well that can walk people through it. And, uh, they've always been super accessible, uh, for us. So we've, we've certainly been appreciative of all of those things.
Lindsay: (24:20)
And it sounds like a tool that's going to be, uh, usable by somebody with really any level of technical wherewithal. Right. Andrew could, if you could just confirm that for us. So you don't need to be a data scientist to work with your platform.
Andrew: (24:34)
Yeah. That's a great way to put it. We try to sort of boil it down so that anybody can start leveraging sort of spatial analytics without a GIS degree or not being a GIS technician. And I think that, um, there's this sort of common misconception and it's because a lot of the sort of press that, um, local governments and local government projects receive for data-driven work is focused on a lot of the more advanced stuff that's out there. And, and that can be daunting to smaller communities or those without a data team. And quite frankly, that's what I love about the gov launch platform is it's focused sort of on some of the more, I mean, maybe the wrong word, but like mundane or operational value that, that local governments can get in addition to some of those more advanced projects. And so I think that that can be daunting, right?
Andrew: (25:20)
If, if you're a smaller community and you're reading readings from the trade publications, um, and you don't have a data team and you don't have somebody on your team with a master's in data science, you don't need a masters in data science to start using data. And that's where we try to sort of distill our tools down in such a way that cities can just access the property profile, see everything, see a 360 degree view of everything that's happened on that property. That's up to date, there's a ton of value and efficiency that can be gained just by accessing that situational awareness. And then we try to grow our city's data capacity over time as we work with them.
Lindsay: (25:53)
And Andrew I'll stick with you, uh, after working through implementation with about a hundred local governments, as you mentioned across the U S what's some advice you'd share with local governments looking for a solution, like when you offer it told me.
Andrew: (26:07)
Yeah. I mean, I think the first is the point that I just made that, um, that just because you don't have a team of 30 data analysts and a chief data officer on staff doesn't mean that there's not a ton of benefit that you and your various departments can start getting by deploying some data tools. The second. And we touched on this earlier, uh, a lot of the folks that we talked to initially believed that they need to have their data house in order before they engage a data analytics firm. And so they'll say, look like, you know, we've got a two year project to clean up all of our data in X system, or to allow all our data's to think and talk to one another. And so the, the advice is you do not need to sort of do this holistic years long effort to clean up your data to start before you start getting value from it. Um, it getting sort of from, from zero to one, right? In terms of starting to leverage data from across different departments, yes. There is some value in cleaning up your data and you can refine it over time, but that shouldn't be a gaining factor to you starting to use data and starting to break down some of these data silos across government.
Lindsay: (27:16)
Yeah. And that's a great takeaway because I know there's a lot of platforms out there that offers some of the same functionality, but do not offer the data cleanup tool. So they aren't wrong. A lot of look urbans do think they have to spend two years cleaning up their data, but just that's part of the reason why we're doing this podcast series right, is to expose local governments to, Hey, there's products out there that can help you with this. If that's something that your local government needs. And then Sam want to end with you, what are some takeaways you'd like another local government to keep in mind when really searching for vendors to help enable more data-driven decision-making and why you'd really advocate partnering with Tolemi?
Sam: (27:55)
I think for any local government, an important thing to keep in mind is the flexibility and commitment of that partner for data analytics. So like I was saying earlier, things change your data sets will change issues. You face will change, and you, the city needs to change with that, to confront those issues every day, every month, every year. Um, so you need a partner who can be flexible and adapt along with you. There are some data vendors out there, um, who provide their product and they, you know, send their contents and it, it is what it is. Um, those products need to change and evolve over time. And, uh, you know, Tolemi really sticks out to us, you know, cause they're always growing with us, they're always expanding. So they certainly implement our data and help us clean and put it in the building blocks.
Sam: (28:42)
But they're also, you know, asking us about new features. You know, what else could we use? And they help us set alerts on, you know, acquire new data sets like pre-foreclosure and foreclosure filing data sets that we didn't have access to on our own. And then, you know, always asking for feedback and always listening to try to make changes to the product as quickly as they can to really help us improve our processes at the end of the day. So I think for any local government is looking at a vendor for data analytics. You know, those are the things to keep in mind is, is really the flexibility and that thinking and patience to grow and change with you.
Lindsay: (29:20)
Well, I want to thank you both for being here today to share your important work with the wider community of local governments, looking for tools to engage more with their data and to really work more collaboratively and informed and efficient way. Andrew, I think really the takeaway I get is you can start your data driven work today that it does this doesn't need to be this long drawn out process. There are tools out there that really make it easy to gain these insights quickly using data that you already have. And Sam, I really appreciate you coming on to share your innovative work in Albany. So keep up the exciting work and best of luck to you, Andrew, on behalf of Tolemi.
Andrew: (29:58)
Thank you very much, Lindsay.
Sam: (30:00)
Thank you, Lindsay.
Lindsay: (30:02)
I'm Lindsay Pica-Alfano and this podcast was produced by Govlaunch the Wiki for local government innovation. You can subscribe to hear more stories like this, wherever you get your podcasts. If you're a local government innovator, we hope you'll help us on our mission to build the largest free resource for local governments globally. You can join to search and contribute to the wiki at govlaunch.com. Thanks for tuning in. We hope to see you next time on the Govlaunch podcast.