The Garage by Sonatus

Recorded live at CES 2026 at the Sonatus booth, host John Heinlein interviews Takayuki 'Terry' Nakamoto, Director of Electrical, Electronics, and ADAS Engineering Department at Nissan Technical Center Europe. The conversation explores how NTCE develops vehicles manufactured in the UK for global markets and discusses the challenges of traditional vehicle development processes that rely heavily on physical vehicle testing. Terry explains how their partnership with Sonatus is revolutionizing their approach through two key AI solutions: Sonatus Collector AI, which enables remote data access and customizable data collection policies, and Sonatus AI Technician, which provides expert-level diagnostic guidance. These tools are helping Nissan reduce development time, minimize the need for expensive preproduction vehicles, and accelerate their start-of-production (SOP) cycles while maintaining quality standards. The interview showcases real demonstrations of the technology and highlights the significant time and resource savings achieved through this digital transformation approach.

Chapters:
0:00 Introduction to the Podcast and Guest
0:24 Efficiency
1:04 Terry's Background and Experience
3:43 Overview of Nissan Technical Center Europe
6:22 Digitalization Initiative at NTCE
7:26 2026 Nissan LEAF
7:59 Challenges in Vehicle Development
11:20 Improving data collection with Sonatus Collector AI
12:45 Dynamically adaptive data capture
15:21 Data Analysis with Sonatus AI Technician
17:38 Making every engineer an expert with AI
19:37 Efficiency gains in problem diagnosis
21:20 Conclusion and Reflections

Creators and Guests

Host
John Heinlein, Ph.D.
An experienced technology and marketing leader, John brings his background from startups and established companies to Sonatus. He worked for 14 years at Arm, most recently leading Automotive Partnerships for North America where he engaged OEMs, Tier-1s, and others to deploy Arm-based solutions into automotive applications, including autonomous vehicles. His team was integral to launching the SOAFEE industry initiative for software-defined vehicles of which Sonatus is a member. Earlier he served as VP and Chief of Staff to the CEO and led a group responsible for competitive strategy. For three years, he was VP of Corporate Marketing where he led centralized outbound marketing, spanning marketing campaigns, press, events, web, digital marketing, ecosystem programs, and working closely with investor relations. Prior to Arm, John had an 11-year tenure at microprocessor startup Transmeta where he held several senior roles spanning business development, marketing, and customer success, among others. John earned his B.S. in Computer Engineering from Carnegie-Mellon University and an M.S. and Ph.D., both in Electrical Engineering, from Stanford University.

What is The Garage by Sonatus?

The Garage Podcast from Sonatus brings you conversations with thought leaders from around the vehicle technology space discussing far-reaching topics about software innovation in vehicles.

These episodes will include industry experts, whether from Sonatus, or from our amazing partners across the industry, all of whom will share their Ideas and their outlook for the most important topics in vehicle technology. Episodes span from more technical topics, to business evolution, and market trends. Join us and learn about the future of vehicle in The Garage.

Today in The Garage,

we're recording live at CES
2026 at the Sonatus booth.

My guest today is
Takayuki Nakamoto,

who's Director of
Electrical, Electronics,

and ADAS engineering department
at Nissan Technical Center

Europe or NTCE for short.

Today's conversation, discuss
how NTCE develops vehicles

manufactured in Nissan UK for sale
in Europe and around the world.

We discuss the challenges
for developing vehicles to

production and how we can
accelerate the vehicle SOP

cycle using advanced AI tools.

It's an exciting
conversation. Let's go!

Welcome to The Garage.

I'm John Heinlein, Chief
Marketing Officer with Sonatus.

We're here recording
live at CES 2026,

and our guest is Takayuki
Nakamoto from Nissan Technical

Center Europe or NTCE for
short. But you go by Terry.

Yeah. Please call me Terry.

Terry, welcome to The
Garage. Glad to have you.

Thank you for having me.

You've got to start by telling us
a little bit about you personally.

I'm Takayuki Nakamoto.
My nickname is Terry.

Everyone calls me
Terry in the office.

So feel free to
to call me Terry.

So I'm Director of Electrical,

Electronics and ADAS Systems
Engineering Department in NTCE,

Nissan Technical Center
Europe. We are based in the UK.

And a little bit
about my background,

I originally started working
in Nissan in Japan as a

BCM engineer, body
control module engineer.

And then I've been

in body electronics almost
until throughout my career.

Okay.

I've experienced BCM,
body electronics,

body control module.

I did the battery
quality, power management,

IKey keyless entry, etc.

I also did the systems
engineering promotion in the

within the company between
with Nissan and Renault.

After that, my career
slightly changed to the more

connectivity side.

I became a manager as a
of the AIVC development.

And then after that, I
decided to come to the UK as

EE manager, and now here I am
as a director of EE and ADAS.

UK is such an interesting
change from moving from Japan.

We're going to get into that in a little
bit about when we talk about NTCE.

Yeah. But first, tell us
about a fun fact about you.

Well, I'm a runner, a
little bit extreme than an

average runner, to be honest.

So I'm I'm joining a
46 mile trail race.

Forty six miles! What is it?

72km, seventy
Something like that.

Yeah. Incredible.
And it's not just me.

My one of my senior
engineers, Sarah,

who is with me in the CES,

is also joining this race.

So needs some management team or

needs some project
member for the

Sonatus project is a
little bit extreme.

That's fantastic.

A trail ultra marathon
is already incredible,

and then to do it on the trail adds
additional level of of difficulty.

So hats off to you.

It's a big challenge
for me as well.

I what's your longest to
date so far? Longest race?

Longest one is
called the Strongman

Triathlon racing.

Which is slightly less
than the Ironman racing,

but that's the
longest I've done.

That's wonderful.

Well, I'm a runner and
an athlete as well,

although I'm not a
very good runner.

You're a much better
runner than I am.

But I've done a a lot of racing,

and I did a trail half
marathon some years ago.

I've done one marathon,

but but nothing like remotely
what you guys are doing.

Hats off to you for
such a distance.

You're welcome to join.

So you'll have to tell
us about Nissan Technical Center Europe.

And what's the responsibility of of
that facility and your your role?

Yeah. Sure. Let me start with
the kind of a history of NTCE.

We started

almost forty years ago as
a part of Nissan Global

R&D Center.

We are originally more linked
to the production site up in

the Sunderland, but now it
has grown and playing a big

role, major role
as a global R&D,

developing cars like
Qashqai, Juke, LEAF,

and selling those cars
to not just Europe,

but also to Middle
Middle East, Africa,

Oceania, and so on. So that's
the the role of our company.

And, I mean, that's
how we started,

and how we grew
bigger up to now.

And in terms of the role,

our main role is really
to put all the components

and integrate those as a
vehicle And making sure

everything works as intended.

And I think because as you
have vehicles sold around the world,

there are different
localization standards.

Localization is
not just language.

Sometimes localization
means language,

but there can be different
regulatory standards,

safety standards in different
regions around the world.

You help to handle
those specifications, I think.

Yeah. That's that's one of
the biggest role as well.

We call it as a frontline role,

but we also after
this SOP of the car,

we are also in charge of taking
care of the quality aspect

because we get many
feedbacks from the market.

And our job is to understand
the the issues or the market

concerns and then feeding back
to our design so that the issue

could be fixed as
quickly as we can.

It's wonderful.

And I think you have an
incredibly long title with,

like, four different
things in your title.

So you have to give us your
full title because you touch on

many different
subsystems, I think.

So, again, my
title is Electronics, Electric,

ADAS, Systems engineering
extremely long,

but it involves almost so
many almost all the the

components, which is
driven by the electricity.

So starting like BCM, USM, ACU,

harness, alternator,
sensors, switches,

and plus ADAS system
components is in my ...

So nothing important.

Nothing important
at all. Nothing.

That's incredibly
diverse responsibly.

How do you I I don't know
how you manage all that.

I have a great team. That's
how how how to manage.

Well, I know one of the initiatives
you have is something you call

"digitalization".

And I wonder if you can explain
what some of your goals are and

and some of the initiatives
you're trying to drive.

Yeah. It's a very good question.

When you hear
digitalization or digital

initiatives, it sounds like
it's a customer facing features.

But for us, for NTCE,

that's more about how
we develop vehicles.

It's about using
using more data,

automation, simulation tool, AI,

etc., to make our development
efficient, consistent,

and high quality in the end.

And that's what it's about.

We are trying to drive,

we are trying to introduce
up to date technologies

to our development processes

So that we can make
it better and, yeah,

make the better quality
car with confidence.

That's great.

It's I assume that includes
things like digital twin where

that's appropriate
and so on like that.

Exactly.

And the Sonatus project
is part of that as well.

I'm glad you mentioned that.

You know, we as we're
looking in the podcast,

as we look right out there,

right outside the podcast
studio is this incredible

Nissan LEAF. It's a 2026
brand new Nissan LEAF.

It's been completely redesigned.

But the reason that that car
is here and the reason you're

visiting with us here this week
and and you've been presenting

alongside us is a project we're
doing with NTCE and yourselves

and your colleague, your
senior engineer Sarah,

who's also with us, been
a phenomenal collaborator,

to show how our technologies
can help in the preproduction

phase that you're
responsible for.

So I thought to discuss that.

Before we get into what problem
what we've done in our solution,

I wonder if we could start with
setting up and understanding

what's the kind of the problem?

What's the conventional
approach you use today

historically to test?

And what are some of the
drawbacks and downsides to the

conventional approach?

Okay.

At the high level, our biggest
challenge is managing complexity

within the limited time
time development period.

Right.

So as you know,
like, EE and ADAS,

it's becoming more and
more complex every day.

But with our traditional way
of developing the the vehicle,

it's hard.

It's it's it's just
doesn't scale well.

That that's the major challenge
that we have in in NTCE.

But I think it's not just us,

but the whole industry is suffering
from the same kind of problem.

Sure.

So for for the current approach,

it's heavily relying dependent
on the vehicle testing.

It's a physical vehicle testing.

Which is a major concern for
us because in reality and

we do a lot of testing
during our development phase.

First thing we need to do is to
access to the car and get the

data from the car so that we
can analyze and understand

what's going on on the car.

Yeah.

That is already a time
consuming because if you think

about our global footprint,
we are based in the UK,

but we have a team
in Spain who does

AD durability
testing, for example.

And we also have a
manufacturing site up in

Sunderland in in the in the UK.

And a lot of issues are
detected there over there.

And, again, in order to get the
data from there is a big effort.

Oh, I see.

So but we are under pressure
to deliver the car in time.

So we have no choice than
going getting the car.

Most of the time,

we have somebody who can get
the data from the car and so

that they can send it to us so
that we and then we can analyze.

But for some cases, there is
nobody who can get the data,

and I will have to send to
somebody from my team in

Cranfield up to Sunderland
just to access to the data.

Just to access.

And I think the other thing
that I learned as we were

discussing the other day is
that, you know, you say, okay.

Well, test vehicles,
it's not that big a deal.

It's not you know,
you make cars,

so you make a few extra cars.

What's the difference?

But these are preproduction
vehicles. Exactly.

So they're they're
very expensive.

They're much more expensive
than a traditional car because

you're not yet at the mass
production economies of scale

that would would take.

So then these are
a real cost to you.

Exactly.

And then in case the
issue is really severe,

the the vehicle gets on hold
waiting for somebody to arrive

and get the data,

hopefully hoping that he will
fix the the issue quickly.

Right. So it's a huge
loss for the company.

And that that's where the
value is coming from, actually.

Because if you can reduce
that time to access to the

vehicle, you know, downtime
of the car becomes much less.

Right.

So that's and in the end,

we can reduce the number of
vehicles if that becomes reality.

And Okay.

So so resource intensive,
vehicle intensive, engineer

intensive, time intensive,

flying people in some cases
are driving driving or flying

people to do that.

So

That's a good setup for
the problem. Correct.

Let's explore the solution and
some of the things we're doing

together with Sonatus and
and NTCE to do better.

Let's start with our Sonatus
Collector AI product.

How has that allowed you to
change the way you gather data

about vehicles and
vehicle issues?

It changed completely
the process.

Well, when somebody rings me
saying that this is happening and

please come and fix it,
I'll just open my laptop.

I ask my engineers to
open the laptop. You know?

You can access to the data in about
a minute or or so within an hour.

That's a game changer.

Sunderland is not so close
from our our site. Right.

Right.

It takes four to five hours
just to get there. Right.

So it's a major
change in the process.

We can even access to the
vehicle from from the from

their their home.

Once we had a chance example

had opportunity where we
had to show our Collector AI

to our executives,

and the engineer was working
from home at the time.

But what he did was
from his kitchen,

he just opened the laptop
and then remotely showed how

Collector AI works
to our executive,

and that was amazing.

That's fantastic.

And then another thing
that you've been showing a

demonstration here
that, you know,

we think about data for
vehicles, but, of course,

there's many, many different
data sources, many,

many different subsystems.

And, of course,

as you're testing,

you're not always testing
the same things or you may be

testing one thing and you find
a problem in another subsystem.

So another benefit I think
we're providing you is the

ability to customize the
data you're capturing.

Is that beneficial as well?

Exactly.

What we really want, if we can,

is to upload all the car of all
the data from the car to the

server all the time.

But, unfortunately, we can't
do that because it's too much.

Too much. Too much.

And it's it's more than a
bandwidth of the communication.

Of course.

It's also impacting
the server side,

and the cost is
gonna be too much.

Right.

So but this customization
of the Collector AI

allows us to to modify it.

Initially, we have just a minimum
set of data uploaded to the server.

But when we know that
there's some kind of issue happening,

we can just remotely adjust
the parameters to what we call

policy.

Data collection policy. Yeah.

Exactly.

And then we collect the only
the necessary data for us

to analyze the the issue.

And that's really, really
cool feature that we have now.

And and we're showing a
demonstration of of that

capability, the
ability to adjust it.

We're showing two different
demo stations where you can

literally adjust that data
collection in seconds.

Oh, yeah.

And and I like to to joke that
imagine the car's on a test

track or a test loop
or something like that.

If you don't like the
data you're getting,

by the time you get
to the next loop,

you could have
changed the question.

The car goes on, which
is incredibly responsive.

Because in in
engineering, you know,

we talk a lot at Sonatus about
the engineering design cycle

of, you know,
observe, analyze, act.

And the faster you can go
around that cycle means you can

you can re aim and re aim
and re aim the the proverbial gun

so you get to the target more
quickly versus if it takes a

week or day to do the cycle,

you realize that I
have to ask many,

many times to get
the data I need.

Yeah. Yeah. It's perfect.

It's it's a perfect example
of agile development.

Initially, today's car,
data that we upload

are kind of hard coded.

We do have a feature to
update it afterwards,

but it's not as fast as we want.

Yeah.

But with the Sonatus
Collector AI,

it can be done in a second,
and that's super cool.

Thank you so much
for those kind words,

and we we are really it.

And and everyone, we've
been showing the demo.

We've shown it to hundreds and
hundreds of people over the

past several days, and the
reaction has been fantastic.

But then we go into
the second part.

So the the Collector AI
is providing you better data,

which is fantastic.

But there's also now of
how do I analyze that data?

And and the second part of your
problem is combing through the

data, understanding the data,
interpreting the data to

see what's wrong, and and
how should you fix it.

So the second product we're
working with you on this

project is our
Sonatus AI Technician.

Exactly.

Tell us about how you're using
that and and how that's been

helpful for you.

When we had this idea of solution
of Collector AI and AI Technician,

we knew this is going to work
because from our from our experience,

when we have the data right
data and provide that data to

the right expert within Nissan,
it doesn't take that much time.

But if we don't have
those two pieces together,

that's where we
lose a lot of time.

We sometimes have a struggle having
access to the data, as I mentioned,

but sometimes we don't
have that expert available.

He was busy doing something
else or it could be on a

holiday or whatever.

But with this solution,
AI Technician,

it's like having that
expert always available

sitting next to you.

And we can ask
him any questions,

any queries, etc., to him so
that he can guide you through

how to narrow down
the root cause.

And yeah, that that's
a huge time saving

for us, for any engineers
working on issue.

And not just the
design engineer.

Right.

It can it will also help help the
test engineer who detects the issue.

Also, it'll help the production
quality engineer who detects

also detects an issue.

They always have to query to
the design and design engineer.

So design engineer
is fully loaded,

have receiving so many queries
from everybody if there's an issue.

So this AI Technician
will accelerate the

issue analysis, but also free
up the design engineer so that

he can focus on the
actual design job.

Yeah. Or the more complicated
situations. Exactly.

One of the we showed a number
of different examples here,

and one of the examples you've
been showing is how you can

begin by first combing
through, I like to say,

the haystack and
just more quickly

find the needles.

Looking at what are the
diagnostic trouble codes,

DTC codes that are
active. What do they mean?

Categorizing them in a way
to get a sense of what's more

urgent, which are active
versus which are historical.

So that's a kind of a first
level of improvement of

productivity that
a human can do.

There's nothing
magical about it,

but it makes it much quicker
to get to these patterns.

Yep.

But then the second part,
which is super interesting,

is then you're able to drill
into some specific failure and

say, why is this
failure happening?

And collectively together,

we're able to use your
knowledge base and your

database that's then
ingested into AI Technician

to give you the logic of how we
were able to diagnose the problem.

How how much of a
helper is that for you?

It's big, because
what we implemented,

realized using AI Technician
is is a normal approach for

automotive design engineer,
automotive engineers.

When we have an issue,

we try to understand

the possible causes,
common approaches like FTA,

and that is already built
into the AI Technician.

But unfortunately, everyone
is not a superstar.

He might be just a
software engineer,

not necessarily understand have a
good understanding of the hardware.

Right.

So but having this so
if there's an issue,

software engineer
can narrow down,

can list up all the possible
causes from software point of view.

However, sometimes it's missing
the hardware perspective in in the

FTA. Right.

But with the AI Technician,

it gives you the full view
of the possible causes from

software, hardware to could
be a operational issue of the

customer, etc.

So that is a is a
big help for any

engineers working in this in
Nissan, or not only in Nissan,

but I think it's on also helps
our Tier-1 supplier to narrow

down the cause and
get to the bottom of

the concern.

I love that.

And your yourself and
your presentation and also your

colleague, Sarah, who's
been here with us this week,

I really like how you've
highlighted that one of the

things we've delivered
is how we tell you what's

not the problem.

So a lot of times in
diagnosing things,

half of the battle is figuring
out what's not wrong so you can

spend more time on the parts
that are the potential problem.

So we're helping to
provide, for example,

an indication that,
know, for example,

it's not a hardware problem or
it's not a problem with this or

it's not a problem with that,

that then we can spend the rest
of the time in a much smaller

problem space to
understand the problem.

Is that is that useful to you?

That's very, very useful.

Common approach for for anybody
in Nissan as soon as they find

an issue is to check the
harness, for example.

Right. How is the connection?

Is the harness okay?
Is the fuse okay?

Is the twelve volt battery okay?

And sometimes just try to is
the software version okay?

Right.

But with the this solution,

with the that kind of
guidance coming coming up ina

few seconds, save us you know,
we don't need to do all that.

If if we have the access to the

data and we already know some
of them are already ruled out

from the the FTA.

Right. Save huge amount of time.

That's great.

That's Well,

I know there's such a pressure on
in the industry on time to market.

There's a lot of the historical design
cycle for vehicles has been quite long.

There's a lot of pressure.

Certainly Chinese OEMs are
delivering a faster cycle time.

And so everyone is trying to
see what can they do while at

the same time not
sacrificing quality.

So I think our mission in
working with you was to help

you to pull in your SOP
start of production,

help pull in your SOP cycle
time while at the same time

achieving the quality and

productivity goals you want.

So we're excited to
be working with you.

Me too.

It's we're so grateful for your
partnership and for for you

being with us here at
the show this week.

It's been wonderful to
present side by side with you.

And I think we both
learned from the process,

both from what you've

done and also the great
questions we've had from the

many customers and many
visitors we've had.

So just my thanks to you and thank you
for joining us on the podcast today.

You're welcome. Thanks
for having me here.

It was a really, really
exciting week for me.

Thank you.

If you like what you're
seeing on this podcast,

please like and subscribe to see other
episodes like this in the future.

And we look forward to seeing
you again in another episode of

The Garage very soon.