Driving Innovation by Sonatus

This podcast delves into the revolutionary role of AI in the automotive industry, particularly through Sonatus's AI technician builder. Steve Stoddard, the product manager, highlights how AI enhances the vehicle ownership experience by addressing misunderstandings between drivers and technicians. The AI technician not only benefits vehicle owners but also streamlines service for technicians and OEM engineers, fostering customer loyalty. With access to real-time vehicle data, the AI technician can adapt and improve service policies, showcasing a significant transformation in how vehicles are maintained and experienced.

Creators and Guests

Host
Sanjay Khatri
Sanjay Khatri is Head of Product Marketing at Sonatus, Inc., a leading provider of software solutions accelerating the shift to AI-enabled Software-Defined Vehicles (SDVs). He brings more than 20 years of experience in product management and marketing for cloud and edge software across Fortune 500 companies and early-stage startups. At Sonatus, Sanjay defines product positioning and go-to-market strategy for solutions that help automakers deliver intelligent, adaptive vehicles that evolve with changing market demands. His background includes leading strategy and execution across Connected Car, In-Vehicle Infotainment, and IoT technologies. Sanjay holds a Bachelor’s degree in Computer Engineering and an MBA, along with certifications in AI/ML, telecommunications engineering, and content strategy. He is a frequent writer and speaker on the future of automotive software, edge AI, and the rapidly transforming mobility ecosystem.

What is Driving Innovation by Sonatus?

Dig into wide-ranging technical topics about modern vehicle technology with industry leaders, hosted by Sanjay Khatri, Head of Product Marketing, Sonatus.

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Language: en

Welcome to another episode
of Driving Innovation,

the podcast dedicated to
exploring cutting edge

solutions and technologies
driving the automotive industry

into a new era of software
defined innovation.

Today, we're diving into
how artificial intelligence

supported by the right SDV
infrastructure is empowering

OEMs to deliver seamless and enjoyable
vehicle ownership experiences.

Joining me for this
conversation is Steve Stoddard,

product manager for Sonatus's
AI technician builder.

Steve will help us understand
how this innovative solution

leverages powerful AI and
real time vehicle data to

simplify vehicle
ownership and maintenance.

And we'll also explore the
foundational SDV technologies

that make these advanced
applications possible.

Let's get started.

Welcome to Driving Innovation,
Steve. Thanks Sanjay.

I'm glad to be here.
Glad to have you on.

Vehicles today are packed
with a lot of technology.

And they're also
getting very complex.

What are some of the
challenges that this complexity

imposes on people?

Yeah. That's a great question.

I think for drivers,

one of the problems you often
see is a misunderstanding of

vehicle, telltales, the symbols
that show up on the dash

leads a lot of OEMs to be
building these digital owners

manuals to help
understand those things,

but it kinda misses out on what
do those symbols really mean

and what should you
actually do about them.

I think for service technicians,

a lot of the digitization leads
to you have to replace entire

parts and more confusion around
the proliferation of DTCs and

signal codes and what
do those things mean.

And for OEMs, a lot of times they're running
into issues where across the entire fleet,

they can't gain insights
into what's actually happening and

what sort of, issues are emerging
and so that they can, avoid recalls.

Well, we're here to talk about the
Sonata's AI technician builder.

So I'm assuming you're gonna
tell me that a lot of these

issues can be resolved by
something like an AI technician.

So help us understand what the
AI technician is and also help

us understand what the builder
part of this solution entails.

Yeah. Absolutely.

So one of the things that
we found out is that,

many of these different, people,

different users of of these
sorts of tools don't have good

insights into real time
information about what's

happening with their vehicle.

You know, there's a lot of
advances in AI out there today.

And I think if you have a
problem with your vehicle,

you can go ask Google
or query ChatGPT,

but the problem is you'll get
answers that are based off of

sort of the Internet,

and what they think is
going on with your vehicle.

What's really missing is
that vehicle connection part,

the data connection, and,

the access to that information
underlying there in order to answer that.

And so one of the things
we find is the underlying

technology that's required to
enable these AI technicians

really relies upon
software defined vehicles,

the ability to collect data,
things like, Sonatus's product,

collector AI product,

as well as the ability to take
action in the vehicle really

helps to advance and make this
capability available for for a vehicle.

Before we talk
about some of the,

underlying technologies,
you mentioned SDV.

Obviously, AI is involved in it.

Let's focus on what the
AI technician can do for

the different types of users that
may potentially interact with it.

I'm talking about the owners,
the service technicians,

and even the OEM engineers.

Yeah, absolutely.

So those are three
very good use cases,

intended users for
this type of product.

For users, for
drivers of vehicles,

the owners of the vehicles,

one of the things that an AI
technician can help them do is

to understand things that may
be going on in their vehicle

that are not as readily available
or easily understandable.

So you can imagine the scenario
where you have an issue going

on with your engine, but a check
engine light doesn't come on.

AI technicians can help
gain insight into what's actually

happening there and provide
recommendations for an owner

whether they should bring
it in for service or not.

And when they do that,

they can also provide data to
the service technician ahead of

time so that they can more
easily diagnose what's

happening with the vehicle and
have the right part on hand

when you bring your vehicle in,

as opposed to having to
come in three weeks later,

once the part finally
arrives and, you know,

being out the use of your vehicle
for for a long period of time.

And for OEMs, it enables the ability
to gather that data from that,

from the fleet level all the
way at the service locations in

order to see these
issues that are emerging,

and maybe better understand
what's happening with their

fleet so they can make
improvements for the next

vehicle generation
or avoid the recalls,

that might happen otherwise if
the if the issue proliferates.

I can see how this would
incentivize me as an owner to

visit the OEM branded,
service shops,

given the fact that they're
gonna have the information that

the AI technician collects.

What are some of the overall
benefits for not just the user,

but also the OEMs that a
solution like this would provide.

Yeah. Absolutely.

So you you hit the nail
on the head, definitely.

Having this kind of insight
makes the service experience at

a dealer owned service
shop much more streamlined,

much more efficient.

So their service operations
can be more efficient.

But also, I think for the OEM,

it really leads to a
feeling of satisfaction,

customer satisfaction with that process
and the whole ownership experience.

So it leads more to customer
loyalty and the knowledge that, hey,

I'm gonna stick with these guys
into the future because I have

such a good experience
when I own this vehicle.

My next one, I'm gonna
buy from the same company.

Right. Right. Now we talked
about the AI technician itself.

And just to be clear,

Sonatus isn't actually
building the AI technicians.

That's where the
builder part comes in.

So help us understand a little
bit more about that part of it.

Yeah. Absolutely.

So one of the things I
mentioned earlier is that,

a lot of OEMs are exploring
these digital owner's manual

type of applications or the
in vehicle virtual assistants.

One of the things that we
find there is that you have to

customize these things for each
vehicle because there's a lot

of specific domain
knowledge for that vehicle,

whether you go from one model to
the next, one trim level, etcetera.

So in order to
make that scalable,

you really have to have
a platform where an OEM a

platform where an OEM can repeat
this process over and over.

And, ideally, they don't have to
be an expert in AI or even

the Vehicle itself in order
to put together the technician

that that has the capability
to know this information.

So that's why at Sonatus,

we built a builder platform
that enables various users at

the OEM to actually create
these different technicians

depending on how they wanna
actually use it for their

customers or internally
within their own,

engineers or even at the,
customer service level.

So they can basically create
these technicians that are very

specific to their vehicle
models, their trim levels,

potentially even down
to the owner level?

Absolutely.

So one thing,

that they'll provide is the
documentation about the vehicle itself.

So these will be things like
the owner's manual or for

something that's maybe
more internal facing.

For service technicians, it's
gonna be like a repair manual,

wiring diagrams, etcetera.

For an OEM engineer
as a user, typically,

you might have an FMEA document or
other fault trees and things like that.

So that constitutes sort of the
engineering knowledge about the vehicle.

Then you wanna pair up the
actual real time data coming

from the vehicle,

and that's where you start
to connect in things like the

actual data from the vehicle
that's gonna be oriented from

the vehicle VIN and
the specific owner,

And then also things
like service records,

your manufacturing history.

All of this is possible.

It's really dependent upon the
different data sources that an

OEM wants to
actually connect up.

And that's gonna depend on
what are the use cases and the

specific users they're going to
build that particular technician for.

So it's almost like having your
own personal AI technician.

I love it.

So we're we're starting to get
into how this actually works.

Obviously, there is
an AI piece of it,

but you can't just
plop AI onto a vehicle.

Right?

There obviously needs to be some
precursors or prerequisites,

that enable these
types of applications

to actually be deployed.

Help us understand what some of
those foundational technologies are.

Yeah. Absolutely.

So one of the items
that's critical, we think,

is the ability to get the
data from the vehicle itself.

So, products that,

sit on the vehicle in
the vehicle network that

communicate across
the different ECUs,

having access to all of
the vehicle information,

not just specific DTCs or
specific areas of the network.

So that's one as a foundational
technology around the software

in the vehicle for
gathering that data,

in real time and and being able to
access that across the different nodes.

A second aspect is actually
getting that data back to the

cloud, which is more of a
data collection product,

something like
Sonatus collector, AI,

which which brings the data
through very lightweight

policies to bring those
back to the cloud.

Once you have those
foundational components,

then you can actually
start to make more,

holistic capabilities and bring
in things like specific AI

models that could run
on that vehicle data.

So you know, something that's very specific
or domain expert knowledge required,

so that it's not only relying
upon the AI technician itself,

but it can call upon these
different agents that can

access those
different tools and,

be able to infer information
about the vehicle.

There's a lot of discussion
nowadays about an agentic model

where you're not just analyzing
the data and and inferring

things out of it, but you're
also sort of closing the loop.

Anything in,

AI technician builder or
the overall infrastructure that,

lends itself to
an agentic model?

Absolutely.

So all those different data
sources that we just talked

about, typically, you want to
build those into discrete agents.

So they're sort of AI specific
modules that are really,

really good at one
specific thing.

Going and looking at this
owner's manual data, for example,

or going and creating
these databases to understand the

signals coming from the vehicle.

So not only does it have to
be able to access the data,

but it has to be able to
interpret that and know, hey.

These signals, especially at
this time, mean this thing.

And relying upon that data,

combining it with the
knowledge about the design documentation,

it can know then, oh, when
I see these types of things,

it's this sort of a problem,

and that's what I need
to recommend to the user.

So those different agents
generally connect up to these

different data sources,
and through that,

you can leverage
these different tools.

One of which, for example,

is to connect to a Sonatus
collector AI product where you

can deploy new data collection
policies based on the,

interpretation of
the, AI technician.

So it could actually look
at the data coming from the

vehicle based on the user query
and actually initiate a new

data policy, deploy
that to Vehicle,

and start collecting data that
was otherwise not even available.

It seems like the AI technician
is almost thinking in real time

in terms of what
its next steps are,

what additional information I need
to make the right, diagnostic,

response.

Let's talk a little bit about some
of the the AI specific technology.

Are these your
traditional AI ML models?

What kind of models
are you using for this?

Yeah, absolutely.

So typically, we're
using LLMs just like,

any many of the other applications
you start to see today.

Ultimately, it's based
on the foundational LLMs,

but we prefer open source,

where we then fine tune and
and bring make those more,

in house models.

And part of the reason for
that is because they can then

perform better on the
specific automotive domain.

A second reason is
that a lot of OEMs,

they wanna host their own
models and know that their data

is protected, both from the end
user perspective for PII data,

but also for the proprietary
data that an OEM might be

providing as knowledge
sources for the AI technician.

So we, build on top of those custom
LLMs and then bring in techniques,

around retrieval augmented
generation and then the agentic

framework, which overall,

we bring in the know how of the
system prompting to make all

those things work
together seamlessly.

Got it.

So just to summarize,

you've got the the AI
portion of the solution,

but you also have the underlying
infrastructure that goes in it.

And you talked
about having a more,

accessible network,
having, you know,

common data exchanges for the models
to to feed the data into the models.

I would imagine this is where
things like service based

architectures or service oriented
architectures also come in.

So that sort of is the sort of the
SDV part of the the overall equation.

Yeah.

Definitely the in vehicle EE
architecture plays an important

role And having access to
all of those different data

sources, it allows you to
bring in things like, you know,

just the general telemetry,
but also DTCs, log files,

all those sorts of things,

even the network traffic
data that can be useful,

particularly if you
think about, like,

cybersecurity and some of
those types of applications.

So it's really important
to have you know,

the more modern the
architecture is,

the the sort of more capable that these
AI technicians can be, definitely.

Excellent.

And, this is all described in
the latest solution brief that

we've just published, the AI
technician builder solution brief.

So thank you, Steve.

This has been very informative
and we look forward to having

you in another driving
innovation episode.

Awesome. Thanks, Sanjay.
It was a lot of fun.

Sonata's AI technician builder
is a great example of how SDV

technologies and vehicle AI
can help OEMs transform vehicle

ownership experiences,

taking the hassle and stress
out of vehicle maintenance and

repair while building brand loyalty
and earning lifetime customer value.

Download the AI Technician
Builder Solution Brief at

sonatus dot com for more
details and schedule a demo to

see it in action.

Thank you for joining us for this
episode of Driving Innovation,

and we look forward to seeing
you in another episode.