Hi, my name is Daniel Myers
and this is another episode of "Powered by Snowflake,"
where I interview technology leaders
who are building businesses and applications
on top of Snowflake.
Today I'm interviewing Frédéric Robinet,
the CTO and co-founder of Vianova,
a data platform built on Snowflake
that uses connected vehicle data
to help cities and mobility operators
build more efficient and sustainable transport systems
for people and goods.
Frédéric, how are you?
Good, and you, Daniel?
Awesome.
So I want to learn more about you as a person,
and how did you get started in this space,
and why did you start this company as a co-founder?
Yeah, that's a really good question.
Thanks for having me in this interview, Daniel.
So why I joined Vianova and I co-founded this company?
Because I kind of touched the mobility space,
while I was in Renault-Nissan-Mitsubishi
as a lead platform and connected architecture for vehicle,
and I had the chance, you know,
to enter some robo-taxi vehicle around Yokohama,
because for OEMs it's really important
to have electrical vehicle,
connected vehicle, autonomous vehicle.
So those are the three pillars,
and this is where I entered this mobility space,
and I was thinking, wow, it's huge, it's big,
it will change our life soon,
but maybe we cannot notice that,
but tomorrow we will have a lot of new vehicle generation
running 24/7 in the cities,
helping us to move from A to B with a seamless experience.
So yeah, that's when I was completely convinced
by the mobility space.
And recently in Europe,
we saw an increasing number of micro-mobility providers,
you know, coming to the street,
proposing their services with moped, bicycle,
all the free-floating vehicle
that you can usually find in big European cities.
So it was welcomed very well by citizens,
but at the same time,
it was kind of challenging for cities,
because they see an increasing number of devices
on the public right-of-way.
And people also started to complain,
because there was some chaos in the streets.
So we saw that as an opportunity
in terms of helping the city to better understand
how the micro-mobility behaves,
what are the trends, the patterns from mobility hubs,
usage of the mobility mix,
and also give the provider
a possibility to show the city
that they are compliant to their regulation.
Awesome. Awesome.
So, can you show us a demo today
of the platform that you've built,
and kind of explain how you're solving that problem today?
Yeah, sure.
So let me share my screen.
So this is our dashboarding.
We are putting a lot of effort in the user experience,
because we think this is super important for the client
to have something that is accessible and easy to use,
but also at the same time,
that is showing the values and the KPI
that they are looking for
in a really fast and efficient manner.
So in this example, it's a demo environment for Zurich,
that you can see that we are providing
a really good map visualization.
So you can see the heat map of the devices,
where are the devices in the Zurich city.
You can also click on them,
know the device status, what is the latest information.
Have also general trends,
the number of devices across times,
the fleet availability,
which is also important for the city,
to be sure that the service is well executed,
that citizens can access all the devices.
We can also show the number of trips that have been taken.
It's always aggregated per hour
in order to be compliant with the GDPR constraint.
It's important for us also
to not disclose too many details
when it comes to people privacy,
so this is something that we are really cautious about,
and we are giving this exactly the visualization
of all the districts and subdistricts.
So generally speaking, in the GIS world,
it's origin and destination.
So what are the most popular origins
when it comes to this particular district or subdistrict,
and things like that.
You can also have this per street segment,
number of trips over a time period,
which is super useful for the city
to understand what are the most-used corridors
across the city.
For example, in order to prioritize their investment
into future or possible cycling lanes,
this is super important for them to take the right decision.
Especially after Covid,
we saw a huge number of temporary cycle lanes
in order to let people cycle and bicycle around the city.
So this is something super useful for them.
We give the exact same thing in terms of parking segments.
So you can see where are the most parked devices.
And this is also something that the city are looking for
in order to avoid crowded streets,
with a lot of micro-mobility devices.
We are giving also the number
across a large amount of periods,
so it can be from one day
to actually the whole history.
And this is where we think also
Snowflake is really helping us,
because at the end, it's a lot of data.
If you think about one device,
could be able to give you like 300 telemetries per trip.
And usually a device is taking
from one to three trips per day.
So at the end of the day, and at the end of the month,
it's a huge number of data.
And we were kind of struggling
with our infrastructure using Postgres.
Then we need to invest a lot of time into,
"Okay, how many Postgres servers do we need?
What could be the size of the cluster?
How can we route the queries?"
And we truly believe that our value
is in the service that we are creating,
rather than, you know, maintaining an infrastructure,
or a cluster of databases.
So this is really where Snowflake is helping us,
because it's so easy for us
to decide on provision the cluster
and the size of the cluster,
it's like instantly applied.
So thanks to Snowflake,
we are able to really invest time in our product.
Another view that is super useful for cities
are the control page.
So here they can see a clear photo or picture
of the actual fleet across the whole city.
They can see potential bottleneck,
where are the unavailable vehicle,
so they can take action, directly contacting the provider,
"Hey, we think there is an issue here.
There are too much unavailable devices."
And also real-time infraction,
so they have the capacity
to digitally create the regulation
that are physically applied.
But then we use the power of Snowflake
to cross geo-fence with telemetries,
And this is super useful for us,
that by joining the beta program,
now we are able to use those kind of
fast computing algorithm,
knowing the number of regulation telemetry
that a city can have.
It's super powerful.
So we can give them in real time
the number of digital infraction to be confirmed,
that they have this view of
what could be the potential problems or bottleneck,
and take action directly.
So, as I said, another module for them
is being able to draw some regulations,
so they can decide,
"Okay, in my city, there is an area
where I don't want any device to be there."
So I can go in my city, start drafting a regulation,
which is also super useful for them.
So they can say,
"Okay, in this area, this is a no-go zone."
Nobody should be able to start a trip or end a trip
for any temporary reason,
some market or, you know,
temporary event happening in the street.
So then the regulation
will be communicated to the operator,
that will directly show that
in the front-end application of the mobile app,
in order to help really the city better organize
the public right-of-way.
That's awesome.
So it's incredibly powerful
to see the amount of visualization
and the amount of information
that you can glean from this micro-mobility data.
And so you mentioned a few of the actions
that these operators are taking,
like for example
they can help prioritize investment in certain areas.
That's really cool to see.
What other examples of outcomes
can people have from this type of data and your platform?
Yeah, sure. That's a really good question.
So we have several use cases.
For example, we help Brussels-Capital
to organize and create what we call the mobility hubs.
So those are dedicated places
where usually provider will drop off the vehicle
in order to fulfill the demand,
because we saw some increasing pattern of,
in front of this train station.
For example, there was a lot of trips starting,
so there is a demand here,
and it will be great if operators can prepare their device
and let them available in this particular space.
And it helps also to better organize
where people can actually find those devices.
It's not everywhere in the streets.
It's really in one place.
They know the place, it's marked everywhere.
So this is the kind of use case.
And after using our product,
Brussels was able to create
between 10 or 15 mobility hubs,
spray-painted across the city.
And we also then give them
the usage of those mobility hubs,
how many devices are starting from there,
to go in which region of the city.
So, better analytics and usage around those mobility hubs.
Awesome. Awesome.
And you touched on, also,
the transition point
of when you moved to Snowflake,
and your thoughts around that.
Can you expand and kind of explain a little bit more
on what your specific evaluation criteria was,
and how did you land specifically on Snowflake?
Yeah, sure. That's a really good question.
So in order to make the best choice,
we had several options in mind,
several also competitors.
But what make us take this decision
was, first, I think the human contact,
and also the availability of people on Snowflake's side.
We had a dedicated engineer to answer our questions.
All the things that we had in mind.
Also, Thomas from Snowflake was a really good partner
to help us make the contract
and follow at each step of our reflection and thinking
by providing answers in the right manner.
So I think it was the first criteria for us
to have this human contact
and people that we can talk to directly.
Secondly, it was for sure the cost,
how much it will cost for us
to migrate everything to Snowflake.
Considering the total cost of ownership,
because usually we think about the running cost,
but also the maintenance and things like that.
So that's why also we decided to go for Snowflake.
And the further thing was
the actual efficiency of Snowflake
in terms of storage, data warehousing,
and also capacity for us, for example, as you see,
to retrieve 12 months of historical data
enough in a fast manner,
which could have taken maybe several minutes
in the previous architecture with Postgres SQL.
And now with Snowflake,
we can do it within 10 or 5 seconds, and it's super snappy.
So those are the three main things
that decide us to go for Snowflake.
As you're building out this company and this product,
what are some of the challenges
that you've encountered throughout the journey,
and what's,
and from this journey, what's next on the horizon?
Yeah, so the first, let's say, engineering milestone
was the scalability,
because if our business goes well,
then the engineering side needs to follow.
So, increasing the number of cities.
Now we have more than 20 European cities
on our platform.
So it needs to grow
in parallel with the business.
Also having more and more providers,
more and more data point for each day.
So this is really the first engineering milestone,
and now we feel much more confident,
after migrating to Snowflake,
that it can scale almost infinitely.
Then it's just a question of cost and pricing,
but at least on the technical side,
we feel really confident.
So the second biggest engineering milestone
was the GIS world.
So, as we are a GIS platform,
meaning geographical information and data analytics,
it's really important for us to be able
to manipulate polygons, shapes, GPS locations.
And now we have entered
the beta program of the GIS Snowflake feature,
and we are super happy.
We managed to reduce calls that were taking one minute
to five seconds
with the new GIS capabilities of Snowflake.
So this is super cool for us,
because it was one of the gray area,
knowing that Postgres is really powerful
when it comes to geospatial information.
But now we think that Snowflake is almost at the same level,
at least for our use case.
And the next big milestone for us
will be machine learning and artificial intelligence.
How can we better optimize fleet.
Our goal, for example, or the city goal
are to reduce the CO2 emissions.
So we are now working on using
our data and machine-learning algorithms
to propose some policies
in order to reduce that by proposing,
instead of taking your personal car and thermic car,
you can choose to have a micro-mobility device
for your one- to five-kilometer trips,
which will reduce the CO2 fingerprint overall.
So this is super cool,
and we are excited to be working on those use cases sooner.
That's awesome. That's awesome.
And so, if one of our viewers today
wants to learn more about you,
or more about your company,
where should they go?
You can go on vianova.io. Everything is there.
You can contact us. We explain what we do.
You have also a partner program,
so you can find all the useful information.
We can plan a demo with you.
And also we have a lot of white papers,
and also we are writing a lot of content
around micro-mobility,
and what we really believe
for the cities and the smart city in the future.
So go on vianova.io, you will find everything you need.
Awesome.
And so for everybody here today, my name is Daniel Myers.
This has been another episode of "Powered by Snowflake."
If you wanna learn how you can build your business
and your application on Snowflake,
check out developers.snowflake.com.
Thanks. See you next time.