Phillip Grimm - Pluvion

00:00:01: Welcome to the Rooted in Change podcast.

00:00:05: Hey, everyone!

00:00:05: My name is Jan and you're listening to The Rooted In Change Podcasts.

00:00:08: This show features European clean tech champions at their solutions to tackle climate crisis.

00:00:12: Today's guest is Philip, CEO & Co-founder of Polyvian.

00:00:15: Those who are regular listeners will know that I have a sweet spot for energy and water technologies which why i'm super excited about today's topic.

00:00:23: Polyvians has developed a wastewater management solution detecting and predicting water infiltrations through networks.

00:00:29: We'll learn more about why this is an issue and how AI can help to solve it.

00:00:34: Welcome Philip!

00:00:35: Thank you for having me.

00:00:37: Well, It's a real pleasure And before we start into todays topic at your company I want to know bit more about you.

00:00:45: so Why don't you introduce yourself To the listeners?

00:00:48: Yeah thankyou very much For this introduction.

00:00:51: My name is Philippe.

00:00:52: i have technical background as an electrician for systems and devices.

00:00:56: I did this at Siemens, a classical formation.

00:01:01: And sitting there in the big manufacturing hall... ...I thought is everything or anything more outside?

00:01:11: So i decided to study geo-ecology and understand complex interactions of our ecosystem.. ..and focused after that on hydrology.

00:01:23: So everything around water and this property fry books.

00:01:27: south germany ever founded the company.

00:01:31: But before that, I was active as a consultant in the water space and international corporation.

00:01:39: As a consultant In Central America but also in Middle East lived several years in Jordan for big water utilities.

00:01:47: Yeah you can imagine they have different pressure on their resource of water.

00:01:50: They had really big problems deep wells

00:01:54: And

00:01:55: so big problems.

00:01:57: Yeah, I can imagine.

00:01:58: And was that also during the time you identified what ultimately became your company?

00:02:03: or how did you end up identifying both of these problems and solutions?

00:02:08: How does this work out

00:02:09: exactly?

00:02:10: yeah maybe in some developing countries They skip some technologies.

00:02:20: For example, they do not have the phone at home but if they have smartphone directly so they skip something and then jump over to technology.

00:02:29: And this is what we saw also in Middle East.

00:02:31: So we used already technologies from remote sensing To machine learning technologies which We in Germany were not used to use it even other Munich where our office was based?

00:02:44: I understood there's a lot of potential when you combine my apprenticeship as an electrician with the water space, as a hydrologist.

00:02:54: And this gave me a lot of ideas and really was beginning off Plyvian

00:02:59: Right!

00:03:01: Now that we sort-of danced around at the company for awhile let's dive into Plyveon.

00:03:07: What is it you do in Plyvia?

00:03:08: what's your solution to bring to market?

00:03:12: It's very simple We identify and localize inflow & infiltration In our sewer networks.

00:03:19: Right.

00:03:20: And tell me, because I was wondering in the preparation for this why is there an issue?

00:03:24: Because you would assume it's sewage water doesn't really matter if additional water comes in.

00:03:32: so This where i got stuck.

00:03:33: Tell Me

00:03:34: Exactly.

00:03:34: but It does!

00:03:36: Because imagine every single drop of inflow For example from brownwater or infiltration From rainwater when its a separate system You have to pump unnecessarily And you pumping it to the treatment plant, and there are treating it unnecessarily.

00:03:53: Now when we know for example that your wastewater network is the biggest economic asset of each municipality I have to maintain it.

00:04:03: so i'd like to know where inflow coming in because There's a leak, root grows something.

00:04:08: So its an indicator.

00:04:10: how my status of pipe on the waste water treatment plant site.

00:04:16: This is the biggest energy consumer of each municipality, so there we have a big leverage in sustainable goals!

00:04:28: So at the treatment plan what you do not like to have it's highly diluted wastewater.

00:04:34: this is what inflow infiltration does and we don't want to have cold inflow.

00:04:40: why?

00:04:41: Because treatment plants are working on a biological base and the bacteria, they like to have it warm.

00:04:48: And be cooling it.

00:04:49: Exactly!

00:04:50: So this is just the problem.

00:04:52: by having a lot of inflow infiltration we decreased efficiency.

00:04:57: We need much more energy...we have put more energy into the wastewater treatment plant.

00:05:02: that's working correct.

00:05:05: Right..and the other part you also mentioned was then obviously the whole volume of water that you need to treat.

00:05:12: Partly unnecessarily also increases, and you need more energy to treat it.

00:05:15: so I think yeah i didn't realize that issue or part of a problem before.

00:05:20: So thats really really insightful makes sense.

00:05:24: And then how do you do that?

00:05:25: Because what I read about here beforehand is AI as involved.

00:05:30: You mentioned your apprenticeship.

00:05:32: training came into play so senses answer all.

00:05:35: What's the tech component for identifying the inflow?

00:05:39: Maybe I explain you what is the typical way we're doing it right now or in the last years before.

00:05:46: So, um... The typical approach to traditional approach is a manual measurement campaign.

00:05:55: It's an aesthetic measurement campaign.

00:05:57: so when going down into the sewer pipes and installing a flow Meter and you're measuring for one or two months.

00:06:06: You putting it out your analyzing in the back office, And some month later their utility gets a result.

00:06:13: so this year doing for some months is That means you only have a static one-time picture when there is heavy rain event in summer.

00:06:22: There, I'm not measuring so no information.

00:06:24: This the problem and this reason why we cannot really work on operations with these manual campaigns.

00:06:33: On other hand side they are very expensive because You have to go down, you have to install them.

00:06:39: Need a lot of maintenance because we can imagine toilet paper and so on they clocking these measurement instruments.

00:06:47: So what we are doing is We have a complete different approach From the hardware side but also from the software side.

00:06:56: Let's take the hardware site first.

00:06:58: We do not need flow information.

00:07:02: The only thing that will be needed Is leveled information.

00:07:06: And why level information?

00:07:08: Because level meter is the cheapest sensor, that's cheapest input data we can find in the sewer network.

00:07:17: This allows us to establish a monitoring really out-in-the-field broad constantly monitoring for the first time.

00:07:24: otherwise it's not feasible.

00:07:28: The price difference between flowmeter and level sensor is twenty times.

00:07:34: so there are big price difference.

00:07:37: It's just not economical to take exactly and senses right?

00:07:41: Exactly, it's not feasible is not possible And this is why nobody is doing it by.

00:07:46: Nobody knows where influence or infiltration has come from.

00:07:49: This Is the pain.

00:07:51: so By this decision To use level information.

00:07:56: We need a solution to Use it to make it Possible deterministic way in a classical hydraulic simulation, because when you are simulating like me as a hydrologist before my studies then say okay I need the exact catchment size.

00:08:15: I need to accept amount of rainwater and soil type etc... And then i'm simulating the level in my sewer pipe.

00:08:26: but we're going vice versa.

00:08:28: We have cheap level informations they measuring But this is contactless.

00:08:34: This is battery driven and you do not have to go down so easy to install much cheaper.

00:08:41: And you measuring the level information.

00:08:44: So what we are doing?

00:08:46: Is we're training the behavior of The switch in separately in dry weather scenarios, and then wet weather scenarios in retraining.

00:08:56: Not only one point your training whole network In traditional and different session alities.

00:09:06: So how is it in this neighborhood?

00:09:08: And in somber, How does that this neighborhood winter?

00:09:11: so we recognize the front pedals under dynamics between these notes.

00:09:17: And therefore be training our machine learning models.

00:09:20: This isn't one architectures not a bond model by the way, it's not an LLM Not large language model which confused sometimes customers.

00:09:30: but Yeah, we have more like a graph causal model.

00:09:35: This is for the orientation in the system and between an auto encoder exactly

00:09:45: And so that ultimately means what you're saying.

00:09:48: it's based on the information that you gather since its constant information gathering and constant analysis compared to manual inspection Maybe, you know at one point in time and then there's sort of information missing before.

00:10:03: And after You're able to Detect the anomaly a sort of in-the system right?

00:10:10: So if it's I would assume that with heavy rainfalls It is.

00:10:16: you would see that this system should behave in one way But it behaves another way.

00:10:19: so you can point to where the inflow Is coming from is not be correct understanding.

00:10:25: Yeah absolutely, so you cannot identify different sources of inflow in infiltration.

00:10:32: For example, a constant and steady inflow of groundwater.

00:10:35: so when your pipe is IN the ground water you have a constant inflow... When there's a leak or a crude inflows.

00:10:42: this we can detect and show it in a hypograph separation.

00:10:46: This really important information for an operator because they know okay!

00:10:51: This is BECAUSE I HAVE A PROBLEM IN MY PIPE But there are different sources, could be also an illegal connection to the pipe.

00:11:01: These illegal connections we can separate from groundwater inflow and then they can say okay in this region my pipe is fine I don't have spending maintenance but i have to look closer to the householders because maybe there's wrong connections.

00:11:18: And what makes really that gain change at a difference Is That We Have A Daily Actual Values And this over several years.

00:11:27: So our monitoring system is minimum three years, a lot of operators using it for three to five years and they receive alarms.

00:11:35: I can give you short information.

00:11:39: use case from one client.

00:11:42: They have in the neighborhood suddenly an alarm.

00:11:48: So what we're giving you is like a heat map green, it's fine.

00:11:51: Red is bad and there are lots of inflow.

00:11:54: suddenly a sub catchment changed from green to yellow two red really fast.

00:11:59: And this operator said What?

00:12:00: What's happening?

00:12:01: that has no rain.

00:12:02: There was nothing happens.

00:12:05: and then he figured out okay in this region telecom right now Is putting the fiber glass fiber cables.

00:12:15: so What happened is, they put it through the sewer pipe.

00:12:21: Imagine

00:12:21: that!

00:12:22: They made two holes in it exactly.

00:12:24: so groundwater was flowing in.

00:12:27: now when you do not have a monitoring system like this...

00:12:32: You would not of noticed?

00:12:33: Exactly and the provider which had made these problems error he's gone.

00:12:40: He is back in this country, you could never receive the money back for this problem.

00:12:46: but in this case...he called them directly and said okay let's look!

00:12:51: And we have to fix his pipe before leaving?

00:12:56: You cannot imagine that there are many monitoring systems really helpful.

00:13:01: That makes it very vividly understandable how Your solution really contributes to sort of the system working better, right?

00:13:12: Because otherwise as you're actually pointing out with fiber they would have put the cable in the ground left again afterwards and You know he probably realized at one point that something is off.

00:13:22: He had look where The infiltration was happening And wouldn't be able to point directly To that instance or whether it's the fiber installation That costed.

00:13:31: but now.

00:13:32: so instead instant moment if your ability to combine other sources information that do I have to say This is where the issue was caused, fixed it and you know.

00:13:40: The system's healthy but also the operator is protected in terms of this huge system.

00:13:46: Exactly!

00:13:47: And

00:13:47: so maybe give us a picture then because your clients use that.

00:13:53: how far have you come?

00:13:55: How has the adoption been?

00:13:56: Because I would assume as you're selling to utilities often they are owned by local municipalities It's relatively conservative, vertically slow moving.

00:14:08: Are they prone to innovation?

00:14:09: or how has that feedback been?

00:14:11: To say hey there is someone coming with an odd maybe background in story and now brings us sort of a data solution.

00:14:20: we are not really sure if it works.

00:14:22: does it work out as well can solve?

00:14:23: Maybe give this bit of back ground into your attraction being at the market entry.

00:14:29: Yeah, no is a really interesting question.

00:14:33: I would not say that it's a stereotype you know?

00:14:35: That this broad is conservative.

00:14:40: but we have lot of clients small operators and utilities because their pain so high.

00:14:49: They tell me Philip do not have any other opportunity or the chance.

00:14:54: I have to repair the kindergarten, put salt on the street.

00:14:59: I have two people and one of them is leaving the famous silver tsunami because mostly working in the sewer space they are really close to get retired.

00:15:17: this was problematic.

00:15:20: They do not have any other chance.

00:15:22: And they are looking for increasing their productivity, to increase in the efficiency... ...to give them priorities.

00:15:30: what our monitoring system is doing?

00:15:32: To say look at this region first!

00:15:35: We know you have to maintain all your sewer pipes but sometimes in Freiburg we have eight hundred kilometers of sewer pipes In Berlin, you have more than ten thousand kilometers.

00:15:49: You cannot go down and make an inspection of every single meter per year!

00:15:55: It's not

00:15:56: possible.

00:15:56: And

00:15:56: it is a question for priorities right?

00:15:58: Like where do we allocate those finite resources?

00:16:00: so I think that's really good example again to say look start where its most needed.

00:16:05: Yeah...and false priorities cost your lot of money because when you

00:16:09: have a leak

00:16:11: Exactly on the other side A leak gets bigger because when gravity is flowing in, then a lot of sand is going into the pipe.

00:16:20: You have an hole under your pipe and then the sewer can even collapse!

00:16:24: And this is really the worst case scenario.

00:16:27: so... false or wrong priorities, decisions then you have to pay the bill.

00:16:33: This is really problematic.

00:16:34: so because of this pain and need we had good chances to start with our first product with Water Plus, the SAR solution for infallowing interpretation.

00:16:48: What we recognize is that most clients, right now the first ones are small and middle ones.

00:16:57: It's not a big cities.

00:16:58: First of all you as startup always have problem at beginning You need references And before going to city like Berlin or Munich We had give them some examples.

00:17:09: This why started in small regions where proved our technology And what we even did, we proved our technology by comparing and testing it with the traditional measurement campaigns.

00:17:24: So they used... They gave us historical data that was made in their measurement campaign because they didn't believe this machine learning system is working.

00:17:35: but all little information of course!

00:17:39: Now give me some hotspots.

00:17:41: where is the information coming from?

00:17:44: Yes, we found it out in the same way and this was like a breakthrough.

00:17:52: Yeah

00:17:52: I can imagine.

00:17:53: And yeah i think that's really good sort of summary to say look We're actually able To deliver with data you provide.

00:18:03: they put You on the spot.

00:18:10: that sales process and business model worked out afterwards.

00:18:13: I mean, you described it as quite granular or that you target many municipalities?

00:18:21: How do look at?

00:18:22: Germany's only solution for now is expanding internationally.

00:18:25: where are they?

00:18:28: So it's not a Germany only solution and we do not have direct B to C business model.

00:18:37: We have a P-to-B business model, what does that mean?

00:18:41: We offer sensor manufacturers but mostly engineering offices our solutions so they can integrate machine learning models into their existing platform utilities and operators.

00:18:59: This helps us in the sales process, of course because they are outside every day drinking at every trade show several views with them.

00:19:06: They know each other.

00:19:07: And this sector The water sector It's critical infrastructure.

00:19:15: There is no space for all.

00:19:16: Let me test If you're drinking what I

00:19:19: know.

00:19:19: it's not possible Start up from Freiburg or Southern Germany like hey here we are No one's waiting Exactly.

00:19:27: And this is why you have to work with trusted companies, they worked with these utilities and municipalities several years... ...and they know each manhole by name!

00:19:41: They really know the differences in the system.

00:19:44: This is very important.

00:19:45: By working with platform operators We received a lot of historical data, which is great for our machine learning models.

00:19:54: They love it!

00:19:55: They have lots of data

00:19:57: and

00:19:58: they split up our mode at the end

00:20:01: Right.

00:20:02: yeah this was really helpful as clarification because I always under the impression that you would sell directly to the utilities.

00:20:06: but obviously if have that partnership approach, you know it makes your route to market a lot easier.

00:20:12: It's a lot easy for you too to sell and you're able to tap into the existing customer relationships.

00:20:17: um and as you readfully say I guess it's very trust-based ecosystem... As many are obviously.

00:20:23: but uh for sort of water is maybe even more critical than other resources.

00:20:31: i'm thinking as much before energy.

00:20:36: You can often find a different solution for energy needs in terms of your PV or wind supply doesn't work out.

00:20:45: Then you generate energy from fossil fuels if you really need to, battery backup and so on.

00:20:53: but with water it's one shot right?

00:20:55: It either clean and works or not.

00:20:59: there is no opportunity important distinction that you're making there.

00:21:07: Yes, and you cannot switch it off.

00:21:08: this is what we saw in COVID yeah?

00:21:10: You can close stores or supermarkets.

00:21:14: almost every business model changed during these times.

00:21:17: but drinking water supply and waste water supply continuously have to operate.

00:21:24: It has to be working.

00:21:26: This is essential.

00:21:28: Yeah And you said something interesting before Follow up on as well, that your first product water plus is out in the market and working.

00:21:38: Will you expand?

00:21:39: That's product portfolio.

00:21:41: and one point how does that look?

00:21:42: absolutely so for us.

00:21:44: what a class it only to entrance.

00:21:47: this is only The First Product of these intelligence layers to establish them monitoring because At the moment When we are complying treatment plans with the network, treatments planned are really good measured and supervised.

00:22:07: In the network we have a lot of dark spots And right now we're entering in this area of monitoring.

00:22:16: We've got a game-changing moment that has cheap hardware technology.

00:22:28: On the base of our information on the train models, we already saw that you also can give our clients' information on blockages for example which is a big issue.

00:22:41: In Germany yes but even more in UK for example and Australia and US.

00:22:47: so there you have to famous fatbergs yeah?

00:22:49: We have to clean them.

00:22:50: they produce it at lot costs And you need a lot of people to really make this, uh... To clean the sewer pipes.

00:22:59: So there's always cost behind it.

00:23:02: if we're talking about costs The biggest motivation at the end and these kind of solutions We like give our clients on top of monitoring layers

00:23:15: Right.

00:23:15: Yeah, it's super exciting and really insightful.

00:23:17: I mean we've all heard about these phenomena that you just described coming out of the UK and The US mainly but i guess they never really thought about how to identify before It happens.

00:23:28: And hard to fix the problem in the first place doesn't lead To those blockages going forward?

00:23:38: If You were to paint a picture where you and plebian are three to five years.

00:23:44: How does that look?

00:23:45: I mean, for now maybe say a few words also on how many you are and when you start sort of where you are or your journey then way want to go going forward.

00:23:56: Yeah

00:23:57: So we have seven people right now.

00:24:01: It's not a KPI increase stuff.

00:24:04: No it is Not really needed Right?

00:24:07: yeah

00:24:08: more important has good team a good working team and have focus in priorities.

00:24:14: And these are, they should be transparent and clear for everyone.

00:24:18: so by the speed-to-be business model we can focus really on machine learning on AI development of our products.

00:24:32: We already made our experience in different markets and European markets, especially the UK.

00:24:43: In Italy and Spain.

00:24:45: these are really interesting markets where we're already in contact with resellers and partners.

00:24:51: so mostly engineering offices is scaling and selling out a solution there.

00:24:58: If these markets are running, then it makes sense to also have stuff in this regions for better support.

00:25:07: This is where we really see Plovin in the next years.

00:25:14: Yeah that's really insightful.

00:25:18: I can personally relate with you.

00:25:20: That number of people isn't a KPI as long.

00:25:23: he delivers really outstanding work that moves the needle for people, and especially in these times with AI powered solution.

00:25:34: I guess a focus sort of is on efficiency or data quality much more than maybe few years back where it was important to raise big rounds fast in order to hire people have manpower then scale?

00:25:51: That's not needed at the same extent anymore

00:25:55: exactly.

00:25:56: And how do you see this is ultimately sort of a, cause.

00:26:01: imagine it's as the SAS model right?

00:26:04: It's a software solution.

00:26:05: A model.

00:26:06: what's the end game for you?

00:26:10: I think because also saw that few years back you did close your funding round.

00:26:15: so is it structural normal BC case or do?

00:26:22: Well, a different type of business model in terms of scaling and expansion.

00:26:27: What's your take on that?

00:26:29: No definitely it is at the VC case.

00:26:33: our first round we did in two thousand twenty four.

00:26:37: Our pre-seed our seat be closed last year in December.

00:26:41: uh seven digit round.

00:26:43: this was the first closing and we still have to second-closing opportunity.

00:26:47: so if there is somewhat out of their um then contact me.

00:26:52: And yes it's a VC case in, but this is absolutely what we see also in that underwater space.

00:26:58: ah in them in the area.

00:27:00: So operators big engineering officers are technology provider.

00:27:05: They expand their solution, they have a lot of acquisitions and there is a lot movement.

00:27:11: There's like gold rush in the water industry because we recognize that water is not only for human important, this industries so important as for agriculture are just so important.

00:27:24: And talking last month about chips production You need a lot of water as well, not only energy.

00:27:33: So you need good and clean water.

00:27:37: so there is... Yeah!

00:27:38: There's a lot discussions in.

00:27:40: Water availability but also cleaning off it keeps high important

00:27:48: yeah?

00:27:48: And I guess what you mentioned at the beginning was that idea about critical infrastructure right?

00:27:54: I mean, you also mentioned the COVID pandemic which is another good example of how we out of a sudden had those different job categories right?

00:28:06: The ones who were relevant to keep our system as society alive enough and running an energy in water and healthcare.

00:28:13: They they were part of it And then other jobs weren't at some point Which i found really interesting In terms of looking at from societal impact.

00:28:24: And then secondly, I guess this whole question of how do we... ...few to prove our infrastructure and especially in Germany but also a lot of other regions across Europe and the globe.

00:28:36: This is a key question going forward sort-of How would be built resilient infrastructures where even if they are?

00:28:43: I don't want you say attacked But somehow disturbed is maybe the better phrase, we can detect this early and fix it.

00:28:51: And I guess sort of what you bring to the market is really that instead of flying blindly throughout the night... You have that vision with an example which he gave earlier where the fiber network reacts more or less instantly, because it was changing from green to yellow-to-red fast and you're realizing something is off.

00:29:12: And I can see what that is.

00:29:13: then fix it.

00:29:14: so i think that's a really good example of an important solution for us as a slide.

00:29:19: Yeah

00:29:20: at the end there are several factors.

00:29:22: Chlamychase also has a factor on a very sensitive drinking water area or trinking and water networks in some parts of Europe already too warm.

00:29:33: This increased the risk of dangerous bacteria, so you need solutions for that.

00:29:41: You mentioned the risks of attacks on infrastructure as though we really needed good security standards.

00:29:54: from the wastewater perspective, there is so much potential still out there.

00:29:59: because we talked about volumes.

00:30:02: But now think about quality.

00:30:06: in COVID- we recognized by analyzing the waste water you get good robust numbers of the virus.

00:30:18: even establish a monitoring or prediction models based on that.

00:30:21: And this is what we know, for example to find out some drug kitchens are already used in the wastewater space.

00:30:31: so there's lot of potential by using quality data and it would be next step combined volumes with quality.

00:30:40: Right again its one thing you don't really think about.

00:30:44: I was really insightful during the COVID pandemic to see that people analyzed the wastewater too and identified the virus load, something you would never have thought about in first place.

00:30:55: That is a better indicator than official testing numbers because difference was quite stark with ongoing infections from the waste water were higher.

00:31:06: then what's reported on the official number of tests?

00:31:10: I think again it helps keep society healthy and sound.

00:31:15: And yeah, nice to see that you're contributing to that.

00:31:20: I have one final question for you which brings us back to the beginning of the conversation because i think you explained your journey really well.

00:31:28: so say look...I started at Siemens and asked myself is this it?

00:31:34: And realized pro not there's more!

00:31:42: build your own journey, study and you know built your own business.

00:31:47: Which I always find really admirable.

00:31:49: so now my question sort of is what isn't that keeps it going?

00:31:52: What was even at Siemens back in the day that realized or helped to realize that spark?

00:31:59: there's more because a... Another solution would have just been to enjoy that nice, comfortable career at Siemens.

00:32:07: You know do the job you're doing there which is also fine and healthy but it shows a different path.

00:32:15: so what keeps going?

00:32:20: It's always more risky entrepreneurial mindset something many don't have.

00:32:26: Yeah, I did

00:32:30: during my time at Siemens in my vacation.

00:32:32: I did a small volunteer project in Guatemala and i think this was really changing my mindset because it's also very small project to school building a basketball yard.

00:32:47: And but by doing that you have direct feedback of Let's see the client so that you have a problem.

00:32:58: You have direct feedback and your helping, and use C the effect of it.

00:33:02: when you are in a big enterprise like Siemens then you always keep let us hear small number yeah even there but he was starting with your apprenticeship

00:33:11: and

00:33:12: never see the output.

00:33:13: who do not have to go to the whole value chain?

00:33:17: and There in Guatemala, I saw that this is really important.

00:33:23: This keeps me motivating and it's also what motivates me right now as a startup founder because there you see the effect of your decisions.

00:33:40: And talking about inflow infiltration we only talked about the inflow but Exist also is exfiltration.

00:33:50: And if you ask me, this is what matters to me personally.

00:33:54: We cannot co-win the client because nature Sending and build to you an invoice.

00:34:00: but exfiltration is really important because we are contaminating our drinking water.

00:34:05: And if you like to live in a healthy society, and I have us eight-week year old baby boy

00:34:14: Thank

00:34:15: You then.

00:34:16: I'd like to living there in the good environment and not that he's drinking contaminated drinking water By monitoring it, by finding out where the problem is coming from.

00:34:27: I hope i can do my five cents to

00:34:31: it.".

00:34:32: Yeah!

00:34:32: It's interesting that you mentioned this right at the end of her conversation and those small human beings they tend to change the picture quite a bit in terms of personal motivation... You know, a stereotype that people say but I found it also true with my kids.

00:34:54: It adds an extra layer of motivation and purpose to the job.

00:34:58: That now is not just you who don't do your job in order to build an impactful business because thats fun and exciting And if you like working on technology its great challenge.

00:35:09: Those are all very fair motivations at certain point.

00:35:14: And when you sort of arrive at that Junction in your life and realize, oh wow.

00:35:21: You know now there's someone else I need to take care off That mission he just described to say healthy drinking water pure drinking water is a really critical thing.

00:35:32: And thats what i'm contributing my time too.

00:35:35: Thats this very solid mission something worth it.

00:35:38: get up every morning which probably its not an issue anymore with the baby or household but getting out probably not the issue going forward.

00:35:47: Yeah, he's

00:35:49: super active!

00:35:50: Nice.

00:35:51: Well, thank you so much for this really insightful and energetic conversation.

00:35:55: I enjoyed it a lot And thanks to which we're sharing.

00:35:57: then all of best Going Forward will keep rooting For You that It is also the additional products That people bring To The Market.

00:36:05: They Will Contribute To Fulfilling That Mission That You're After.

00:36:09: Thankyou very Much.