July 2, 2025 • 38 mins
By now, you’ve probably participated in a video conference call that’s been recorded and automatically transcribed, with a meeting summary sent to you within seconds of the meeting ending.
The likes of Teams, Otter, Zoom and Fireflies are using artificial intelligence to parse our language for insights and meaning, translating long, meandering meetings into useful summaries.
But Christchurch startup Contented AI is taking this a step further, with its transcription app also mining conversations for information that can be turned into action tables, SWOT analysis, deep dives, and decision logs.
On the Business of Tech this week, Contented AI founders Lucy Pink and Hannah Hardy-Jones explain how they've bootstrapped a company that aims to be the "Canva of conversations". Listen to the full interview. PLUS: Dr Sarb Johal answers my big question of the week: What part of your life should always stay analogue, no matter how smart tech gets?
See omnystudio.com/listener for privacy information.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:03):
Cure and welcome to the Business of Tech powered by
two Degrees Business, where we dive into the latest trends
and stories shaping the world of technology and business here
in New Zealand and beyond. I'm Peter Griffin, and today
we're spotlighting a homegrown AI success story that's quietly making
waves on the global stage. We'll get into the podcast shortly,
(00:26):
but first a new and occasional feature I'm adding to
the podcast where I put a single question to someone,
someone who may have been a past guest on the show,
or maybe someone I think will have a really interesting
take on a tech related issue. This week's question goes
to Saab Johal, the former Massive University Associate professor in
(00:48):
mental health, author, tech commentator, and YouTuber. I had Sab
on the show over a year ago to talk about
the debut of Apple's Vision pro augmented reality head hit Cyber'
is a massive Apple watcher. Cyb really understands human psychology
and he's a real tech enthusiast, which led me to
(01:10):
ask him this question. When I've been increasingly pondering as
artificial intelligence proliferates, what part of your life should always
stay analog no matter how smart tech gets. Here's what
CYB had to say.
Speaker 2 (01:28):
For me, it's the slow, analogue moments that make space
for thought, like scribbling in a notebook or reading an
old paper encyclopedia with my kids and pausing to talk
about what we've just read. It might not be the
most up to day information, but it's good enough to
start a conversation, and that's the bit I care about,
the space to pause, reflect, and just muddle through together.
(01:54):
I live in a world full of tech. I film
with it, edit with it, and even use AI to
help me write sometimes, but not everything needs to be optimized.
In fact, some things shouldn't be. When I'm rising my hand,
for example, I'm not trying to be efficient. I'm trying
to feel what I think. That tiny bit of friction.
(02:16):
The slower pace makes it easier to notice what actually matters.
Because more and more research is telling us that it's
the dialogue between our left and right brains that's important.
The idea of having knowledge but not quite having the
language for it until we make space to allow the
relationship of language and deep knowledge held in the right
(02:39):
brain can eventually be verbalized by the left brain. It's
a slow groping in the dark gradual process, and at
the moment, all I see is AI models trying to
replicate left brain efficiency rather than a dialogue with our
more parallel processing summary of all things right brain. And
(03:03):
even outside of writing, sometimes I'd rather not have tech
jump in with the answer before I've even figured out
the question. There's value in the awkward pause, in not knowing,
in getting a little bit lost. So while I love
tech that makes life easier, I think there's a danger
when it makes things too easy, when we lose the
(03:25):
opportunity to engage, to struggle just enough to grow, to
connect in a more human way, not just with each other,
but with our own selves. So that's why I protect
the analog bits of my life, not because I'm nostalgic,
but because they keep me thinking, and they keep me present,
(03:46):
and they keep me connected with the richness of the
totality of me, and that to me is worth more
than perfect convenience.
Speaker 1 (03:56):
I really love that protect the analogue parts of your
life to keep you thinking and to keep you present.
Great advice from Cyberjohal. I'll put links to Cyber's substack
and his YouTube channel in the show notes. My guests
this week are Lucy Pink and Hannah Hardy Jones, the
dynamic duo behind Contented AI, a christ Church startup that's
(04:21):
reimagining how we capture and extract value from our conversations.
If you've ever left a meeting or an interview thinking
there's gold in there, but how do I actually use it?
This episode is for you. Lucy and Hannah's journey is
a pretty fascinating one. Neither started as a technical founder.
Hannah comes from an HR and mental health background, having
(04:44):
built the well being app Kite after her own personal journey,
while Lucy's path took her from ethical marketplaces to teaching
herself to code during lockdown. Together they've built Contented AI,
a platform that transforms everything from council meetings to client
calls into actionable insights, tailored outputs, and even content ready
(05:07):
for LinkedIn. On the face of it, this sounds a
little bit like you services like Otter, even the transcriptions
available in Zoom and teams services like Fireflies as well,
But Contented has gone much much deeper here to deliver
real insights from interview transcripts or recordings of meetings. We'll
(05:27):
talk about how Lucy and Hannah met at the Ministry
of Awesome's Coffee and Jam event what it's like bootstrapping
an AI company and ar Tairoa, and why they believe
the future of work is all about making every conversation count.
Plus we'll dig into how Contented AI is already helping
legal firms, journalists, and even EWI organizations get more from
(05:51):
their words securely, accurately and with a uniquely Keiwi approach.
Lucy and Hannah were both keynote speakers at Electrify our
tairo last week here in Wellington, a great conference centered
on women founders. I got along to a few sessions
and it really was a top notch event. I'd encourage
you to go next year. So let's get into it.
(06:13):
Here's the co founders behind up and coming AI startup
Contented AI. Hannah and Lucy. Welcome to the business of tech.
(06:36):
How are you both doing good?
Speaker 3 (06:38):
Really well?
Speaker 1 (06:38):
Thanks? So I've heard just recently about Contented AI, and
I'm on a mission to showcase some of the AI
startups that are coming out of New Zealand. I get
the feeling that we're a little bit slow, really too,
taking all of these great large language models and then
turning them into businesses, maybe slower than Australia, but this
(06:58):
year in particular, I'm seeing a lot of great companies
as a launch coming up this week for yet another
one in Wellington, So it's starting to happen. The pair
of you really got together. What was it in twenty
twenty three? The content had launched in April twenty twenty three, which,
when you think about it, wasn't that long after the
debut of Chat GPT, which changed the game when it
(07:21):
comes to generative AI. Take us back to the origin story,
after two of you meeting and having done quite a
bit in sort of business, but not necessarily as technical founders.
Speaker 3 (07:32):
Yeah, so we met at the Ministry of Awesome. We
actually a few years prior to starting Contented. We were
brought together as we're both speaking at an event called
Coffee and Jam, which was just showcasing early startups and
their ideas. We were both starting in the sort of
Tiohaka incubator program and it was Yeah, it was just
(07:53):
amazing to meet each other here about what we were
doing with our startups, hear about the problems that we
were solving. We became really close over that time really
just supporting each other as solo founders, you know, like
just having that community and being able to bounce ideas
off each other. And we got to the point it
was really when chetchybt launched that we saw the power
(08:16):
of AI and how it could help our own startup.
So just being able to power up what we were doing,
you know, with this lack of time and resource and capital.
We had suddenly a tool that could really transform what
we were doing. And that's when we decided to come
together to create something to help you know, businesses and
(08:38):
people use this technology. So that was the start of
the journey.
Speaker 4 (08:42):
Really we basically were Chatchybt consultants, you know for a
few months, you know, and we were because it was,
you know, yourself, as a startup founder, like can't mentioned
you're trying to make the most out of anything you get,
and AI was one of them. And so we became
in credibly proficient with chatjibt so quickly because finally we
(09:04):
could create content, we could do research, we could create
LinkedIn posts all based on kind of using a chatbot.
And so when we became really good at it, family friends,
legal firms, schools were asking for our help because we
just with somebody and people that just dived in. What
(09:24):
we found very quickly was a it's good if you're
sort of an individual person and you know what good
looks like, and you can use AI in a great way.
You know how to prompt, you know what is false
and what is true. But when you're trying to roll
that out across an entire legal firm and you're trying
to get people to use CHATCHBT and teach a whole
variety of people, that's when it gets very difficult. And
(09:47):
so we paed back really with chatchept, didn't we because
we were like, actually, we don't actually know if we
love the interface, We don't know if we love the
technology just yet. And we kind of went back to
the drawing board and started to talk to the businesses
we were working with to go, actually, what is it
with your pain points? What is it around your business
that you're wanting to use AI for? Is it actually
(10:09):
a problem? And so even though we were AI consultants,
we hardly ever spoke about AI. We're kind of just
talking about problems. And then that's kind of when Contented
started to become a product. But it really took about
a year and a half of R and D to
get to this point, which is where we're at.
Speaker 1 (10:28):
Yeah, so we're going to get into exactly what content
it does, but really intrigue at this mix of skills
and backgrounds that you bring to Contented. You know, Hannah,
I think the Kite program I'd love to hear more
about that. You've got sort of quite a mental health
and well being sort of background, and then Lucy obviously
(10:48):
debt to Daddy. Interesting to hear about that. So quite
an eclectic mix of different types of businesses that you've
been involved and tell us the sort of the background
to your businesses you were in coming to Contented.
Speaker 3 (11:01):
Yeah, so I started the Kite program. I'd actually come
from an HR psychology background. I'd also really struggled from
a mental health perspective after having my first baby, So
it really changed kind of where I saw myself. And
so Kite was based on you know, tiny steps micro learning.
It was an app. It could be customized to different
customers and different you know eating disorders or you know,
(11:25):
workplace well being, and so that was my whole passion
and I built it like I can hand on heart
say now, like it was built on my own experience
and what I thought people needed, and I did not
enough user research, and I went barreling down this path
of I've got to build this app and it's going
to be a global sensation, you know. And I think
there's a lot of learnings from there. But going through
(11:48):
that process and kind of being I can sell really well,
but I don't think I had really spent the time
to understand the customer. And so Lucy will share more
about this, but you know, that's when our skills come
together really well, because everything that I don't have, Lucy
has and potentially there by way around. So that was
(12:09):
that was my journey with kit.
Speaker 4 (12:11):
Yeah, and I think and Hannah's being low key about
it because you know, the selling and the passion also
helps with landing amazing customers like you know, the National
History Museum in London, you know, being able. I think
me and Hannah really collecked because we are such doers,
like once we've got it in our head that this
is where we want to be and we see the impact,
(12:32):
there's no stopping it, you know. And Hannah's ability to
stretch her impact all the way over to London US
and rally some amazing companies is testament to her. I'm
the opposite in the sense that I loved talking to
everyday people, understanding what it looked like. And as a consumer,
I built kind of an ethical marketplace and built and
(12:56):
started to learn to code based on my own problem,
which was I wanted to know more about where products
were from and if they were ethical, and I spent
a lot of time on Reddit. I'd be talking to
one hundred users around what is it around an ethical
white T shirt? You know, what is ethical? What does
that mean? How do you buy it? Where do you
want to buy it? So I did the opposite, and I,
(13:17):
as a comfort zone, went to building a product and
hardly selling. You know, I just wanted to build this
beautiful product and had the assumption that if you did that,
people would come to you, which is completely the wrong
approach because I think you're nothing without sales or revenue.
That combined we kind of came together. But going back
to Dada Daddy, it was an amazing way for me
(13:39):
to learn about startups and but building a business. My
boss met. He was incredible because he was so passionate
about you know, accounts receivable, maybe not the most glamorous
topic that you saw everyday guy wanting to build some
tech in software and a solution around it and build
an incredible business. So I kind of got a front
row seat that looks like. So that kind of propelled
(14:02):
me into startup world and having the kind of motivation
to do my own thing.
Speaker 1 (14:07):
And I understand it was sort of in the depths
of COVID that you decided I'm going to sit down
and learn to code. What inspired that move and what
was it like sort of doing that at a time
when you might have been sort of a bit more
isolated from the sort of people who are going to
help you on that journey.
Speaker 4 (14:24):
Yeah, exactly. I was during COVID, and it was the
first time I actually had the brain time, and it
was in a privileged position of, you know, living with
my parents who basically were making the amazing dinners, and
I got to spend my nights and days finally building
the software that I couldn't stop talking about. If you
talk to me, if you talk to the team at
(14:45):
deada Jelly, all I talked about was on you in
this marketplace. So it was this kind of perfect stars
alignment moment. What I had to do was I watched
countless YouTube videos. I started to build, I started to
learn to code. Was driven by a problem. So I
think if you if you asked me to do like
a software engineering pay for at UNI, I would have
(15:07):
hated it. But because I was driven by building this
thing that I've always dreamt off, I managed to do it.
And I loved engineering and I loved software and it
was always something that I loved to do and for
that school, and so yeah, I think what I did
find was I hated bugs, I hated checking code. I
had no patience for it. So again Star's alignment. AI
(15:28):
comes along, and I could build quickly fastly, I could
build well, and I could use AI to do all
the stuff I really didn't want to do.
Speaker 1 (15:38):
So yeah, yeah, and you know, I've just built a
website with an AI agent called Replet. It took literally
a couple of minutes. There's a whole host of these
AI agents now, so it's absolutely changing the game in
terms of software development. But Hannah tell us about contented AI,
(16:00):
and you know, it's built around this idea that every
conversation can be turned into extraordinary outcomes. I think that's
how you describe it, and it very much comes down
to voice and conversations. And this is at the heart
of what I do talking to people, doing interviews and
then getting transcripts. I'm using tools like Otter and Fireflies
(16:20):
and even teams to make sense of all of these
conversations that I'm having and get contexts. So all of
these tools were sort of being infused with AI around
twenty twenty three. Tell us about this particular take you
wanted to have on conversations and extracting value from them.
Speaker 3 (16:39):
Yeah, so when we first started, we were doing lots
of different sort of mini projects. Some of them were
voice inputs, some of them were imaged, some of them
were data, and we found time and time again that
the most valuable input into these tools is voice data.
You know, a transcription of incredible words is so much
(17:00):
more meaningful than just some data or a few prompts.
And so we realized that it was conversation, not just meeting.
So a lot of the tools that you'll see will
be note takers. They're very focused on these sort of
transactional turning a meeting into some summaries. We wanted to
take this value of conversation and just really push that,
(17:20):
so we talk about wasted words. You know, in a business,
the amount of words that we say in a day
that are valuable that could actually have an outcome to them,
whether it's turned into content or you know, a proposal
or something for the team to share. You know, this
huge value to that. So that's where where we come
(17:41):
in is it's not about just a traditional business meeting
that needs an output. In our businesses that we work with,
they're using conversation from musings through to team meetings through
to a conference speaking session. You know that there's so
much richness across everything, and we like to see it
(18:03):
being you know, we talk about it sometimes being like
canvas for conversations. It's one conversation asset can turn into
so many different things, and that's what really excites us.
But that's also what excites our customers so much, is
just this world of opportunity from this one conversation.
Speaker 1 (18:20):
You're using some of the top large language models, you know,
presumably from open Ai and maybe Claude and others as well,
and they're really attuned to natural language processing and making
sense off conversations. But what process did you have to
go through actually adapting all of those to your specific needs.
Speaker 4 (18:42):
We were really fortunate that a couple of years ago
a man called Pedal the Fort came on to our
kind of doorstep. It was his last day in New
Zealand on holiday and he saw Contented the sign and thought,
what is this AI company? And it was really early
in the sort of age of AI. So he had
a coffee with me and Hannah which ended up being
kind of a four hour conversation, and Peter had worked
(19:05):
at Microsoft for a really long time and he really
understood our vision which Hannah just mentioned before, which is
seeing conversations being an incredibly rich data source that previously
without AI, was untapped, you know, and people were having
meetings without any traction or outcomes coming from it. So
we contented we're finally seeing that. But to be able
(19:25):
to earn the right to kind of work with businesses,
to do that, you have to be accurate, You have
to have safeguards, you have to work with great models,
you have to have great kind of hallutionin hallucination prompting.
You have to be able to provide all of these
frameworks and the person or the industry to help us
build out. With journalists, we worked with journalists over in
(19:46):
the US to build the kind of first version of Contented,
which was to take kind of five hour council meetings
and turn them into news stories. Because in the US
at the moment, you're seeing a kind of decrease in
publications news agencies. So you've got incredible individuals who are
kind of taking that on. And so we have a
(20:06):
large customer base in the US that users contented to
turn council meetings into news to keep their communities informed.
But in order to do that, you have to be accurate.
So Contented today was built off the back of challenging
circumstances and the sense that I would spend a summer
building and creating incredible frameworks around these llms and choosing
(20:31):
the right llms, and at that stage, every week there
was a new model, and every model would let me
down technically, you know, and I'd still have to build
huge prompt frameworks around these models to make sure that
they were accurate. They were long, and they were good,
good writing. And one of our kind of publications was
the Palm Springs Post, and they had worked with some
(20:54):
incredible publications. They've come from amazing backgrounds, and so his
kind of his perception of writing was incredibly high, so
we had to make sure we were building some great outputs.
So yeah, so we've been challenged across all of our
building and I think that's why people love us is
because our level of accuracy and outputs is next level.
Speaker 1 (21:17):
Yeah, that's you know, it just resonates so much with me.
Obviously in terms of democracy itself, you know, newsrooms are shrinking,
We don't have enough journalists. You know, Luckily there's some
funding through the Democracy Public Journalism funding from the government
that is continuing to allow people to go and cover
(21:37):
council and local court. But there's just too much information
and not enough people to sift through it. So if
you can record all of that and actually make sense
of it in a way that's useful for the needs
of democracy and journalists. So, Hannah, how does that sort
of concept apply to other types of businesses that you
work with? It seems like what mind mapping and business
(21:59):
plan So turning all of those conversations and transcripts actually
into output that's useful for a business trying to decide
where it's going.
Speaker 3 (22:08):
Yeah, so we we're identified in the hub of contented
is sort of some standard outputs that everyone can create,
so a SWAT analysis, a summary, a risk matrix, human
centered OUTPUTSLACK, people's struggles and motivation. So those are across
all of the businesses that we work with. The benefit
is that each business also gets to have their own
(22:28):
custom outputs that we have developed alongside the industry. So
within finance, and within law and within health. So you know,
these buttons that people can create that are very specific
to the conversations they're having in that industry, and we
find that works incredibly well. It makes contented, relatable and
accessible to everyone, and then each kind of customer base
(22:50):
can also have best practice from their industry and kind
of you know, it's almost like having an incredible consultant
coming alongside your conversations and turning it into things. But
they get to click a button, and that's really important.
And I think from a you know, even working with
you know, if someone's trying to get an output from
say chat TOBT, the hard thing is is you're prompting
(23:10):
to the level of you know, you have to put
so much effort into that. And so we make this
accessible that anybody in any industry can literally click a
button and get this absolutely high level output every time,
and there's a lot of comfort in that for people too,
because they don't want to have to do all that
hard yards with a chatbot.
Speaker 1 (23:30):
Yeah, and look, you said earlier that you don't really
talk about the AI aspect of it. You're trying to
make it really simple and seamless. So do you adapt
the app for different industries or does everyone get the
same dashboard to look at? We adapt?
Speaker 4 (23:47):
So a good example might be if you're a mortgage
broker or an insurance firm. They're a really good example
because there's so many requirements and needs and outputs from
just one conversation. So let's say it's discovery conversation with
a couple who are looking to buy their first home.
You know they would create and contented their perfect proposal
(24:08):
back to them to say this is what I'm hearing.
Within the same vein, they've worked with us to create
the mortgage application form and the outputs needed for that.
So from just that twenty minute conversation, they're creating the
form that they will then send to the bank. They're
also creating a compliance checklist, so they need to be
able to show that they've provided the right advice. They've
(24:28):
made sure that they're not a vulnerable client, so they
need to show that they can tick that off. They've
asked the right questions, so they create that and then actually,
because they're asking the right thing and they're providing advice
and on that day they're finding great advice, they actually
then go into our marketing module and they create a
LinkedIn post or a LinkedIn blog to say, hey, if
(24:49):
you're a first home buyer and you're about to go
to auction, these are the things you need to prep for.
And then potentially if they're looking to get in a
new team member or they're wanting to train another advisor,
they could then go and create a cheat sheet to go, hey,
these are the questions I asked, and actually these are
the questions I should have asked too, and create some
internal training so that kind of if you can visualize that,
(25:13):
it's one conversation, like Hannah mentioned before, sweated into so
many amazing assets, and I think for advisors they shouldn't
have to go into LinkedIn to go, shit, you know
what am I going to write about today? And what
does that look like? They're actually they've got the expertise
and advice there in these conversations, and that's what they
should tap into.
Speaker 1 (25:33):
You talk about things like you're creating LinkedIn posts and
that sort of content. A lot of people will probably
be doing that in chat, GPT or maybe even Microsoft
Copilot if they've got a subscription. But we're seeing services
like Contented, which is doing all of that for you.
So how do you position yourselves in terms of saying
to customers you can actually do all of this. You
(25:54):
don't need this proliferation of subscriptions, you can do it
all through our PlantForm. And related to that, how do
you avoid just being seen as a feature rather than
a business a feature that potentially is going to get
built into one of these big platforms like Otter in future.
How do you position yourself so that it's worth having
(26:15):
a subscription to Contented instead of you know, some of
these other big sort of platforms that have emerged.
Speaker 3 (26:21):
Yeah, I mean the big things for us is our
transcription is better than anything on the market. If we
can get a potential customer to experience Contented, that's it.
They don't need any other convincing because it's so clearly obvious,
you know, And it's all those things that in person meetings,
we thrive and you know, being able to just use
your phone and have that being able to analyze really
(26:42):
quickly with noise and accents today you know, multiple speakers,
So particularly in New Zealand, obviously we've got a lot
of EWE lead EWE owned organizations that love us because
of how we treat today a Maori and so there's
that side of it, and then there's obviously just the
unbelievable quality of output which is just incomparable, you know,
(27:05):
And that's a huge part of it. And I think
because you can have it rolled out across a whole organization,
and we're working with some really large New Zealand businesses
because it taps into everybody's roles, you know, and everybody's conversations.
It's so easy to roll that out and it be
solidified and everything, whereas most other tools are just pockets,
(27:27):
you know, and some people love them, some people don't.
So that's where we're really leaning into the fact that
it's just so easy to adopt it too because it
works so.
Speaker 1 (27:35):
Well, right and Lessie, it's clearly very useful for strategic conversations,
risk management, that sort of thing needs are quite sensitive conversation,
So how do you deal with that putting your customers
sort of minds at ease that this stuff is going
to be private. It's going to be it's sensitive information
(27:58):
that it's you know, so how do you store it
and make sure that all of those conversations actually stay private?
But you get these great outputs from them, and I guess.
Speaker 4 (28:06):
We work with the company. So for example, if you
are a high needs customer, you might want to do
things like PII reduction, which basically means you can redact
names before they even hop into an AI model. So
we offer a menu of ways to customize how you
know private, you want these conversations to be honest. We
(28:27):
take our role really really responsibly. So data, I guess
before the age of AI, you know, people kind of
knew what companies did with it, but you know, they
kind of just let it go and happen. But now
you've got these questions like is this company training our
data on AI? And tech firms are having to come
to the fore to kind of deal with this situation
(28:50):
where now a lot of users want to know what's
happening with their data. So as a new company, we
get to work in a world that accommodates this. We
know that the local pizzeria wants to know that their
data is going to be stored in New Zealand or
if closely you know, Australia. They want to be able
to have that, which is before, I guess before they
(29:12):
didn't even have that opportunity. So we offer that to
our customers in terms of where that data is stored
and what that looks like in terms of you know,
risk conversations or sensitive conversations. The outputs we create are
based with their customer. So for example, if it is
a risk matrix, we work with them to go what
actually is risk? How do you infer risk?
Speaker 3 (29:32):
What is risky?
Speaker 4 (29:34):
And so actually every output is kind of pretty customized
to that customer because risk might look a lot different
to another business. And so I think that's where you know,
chatchept goes wrong because if you put in their conversations
and make me a risk matrix, you're you're asking chat
chept to quantify that risk and you don't know where
(29:54):
that's from. So for us, it's a lot around personalization
and using AI to help with that.
Speaker 1 (30:00):
You've got I think over one hundred customers now and
a lot of international customers. How did you go international
as a small New Zealand AI startup based in christ Church.
What was your sort of key drivers of your international adoption.
Did you sort of what goes straight to newsrooms first
and target them or was there a particular segment that
you went after initially.
Speaker 3 (30:21):
Our whole go to market currently, honestly is word of mouth.
You know. We got an amazing sports publishing company in
London as a customer and they had just seen someone
talking about it, you know, online on Twitter from America.
You know, like this is the level of you know,
we'll speak at a conference or we'll partner with a
(30:41):
conference to create like a version of contented for them.
It spreads so fast and so we haven't targeted necessarily
actual you know, geographical regions. It's just been this organic focus,
which is a really exciting part for us into this
next phase, which is when we can target We do
have the capital to be able to really launch you
(31:03):
know into a particular region or city, we can really
nail that. But yeah, it's been an organic process.
Speaker 1 (31:10):
Wow, that's great, And where you at on your sort
of capital journey you're obviously you know, generating revenue now,
which is fantastic. Have you raised money or are you
looking to raise more money?
Speaker 3 (31:23):
We're soon.
Speaker 4 (31:24):
Yeah, we're bootstrapped and proud of it, and we're stoked
because it meant that we've built a business on our
own terms, you know, and we've felt what building a
business looks like, and we know that we can take
a risk and a risk can pay off because we've
got our own capital behind it and we've got our
own team. So we've been able to do this, you know,
(31:44):
for across the last couple of years, and what we're
really excited for, like I mentioned, is to be able
to actually put a bit of capital behind this. So
we will be looking to kind of start the conversations
around an investment across the next couple of months, just
to see if we can find some great investors who
kind of understand our vision, who want to jump on
(32:04):
board and to help us with this kind of next
stage of growth, which will be exciting.
Speaker 1 (32:11):
Okay, fantastic. Well, hopefully someone's listening who really likes the
sound of this business and it has some money to invest.
But just finally, for both of you, where do you
see Contented going and in terms of this sort of
technology around voice and conversations. For instance, I see the
game changer that's coming in it's sort of possible now,
(32:33):
but it's a bit clunky having these new conversations but
then combining that with all of your institutional data and
past conversations to make sense of where thinking has gone
in an organization. So it's you're not just having the
same conversation again and again as new people come into
the organization. You're retaining that institutional knowledge and supplementing it
(32:54):
with new conversations. And I'd love to see more in
that space, but interest in your views on the features
that are coming or that you know you really would
love to see in Contented.
Speaker 4 (33:06):
Yeah, and we're spearheading at the moment, so you can
imagine now, customers trust us with their sensitive conversations, and
trust is at the center of what we do. So
the vision of Contented will always be around trust and security.
And with that trust, it means that we've aren't the
right to be able to build incredible features like horizontal
(33:27):
insights like you just said. You know, you've got a
council that's put through all of their council conversations, that
council meetings imagine if you could go back and create
some insights around, Okay, what we're we talking about? You know,
what were the problems? Where do we keep on, you know,
talking about that same problem. How can we do a
council meeting better? Who is roadblocking? What does that look like?
(33:49):
We've spent the last couple of years, you know, creating
an LTP. Are we getting anyway close to this? You know,
this is the LTP. This is six months of council meetings?
What does this look like? So being able to have
horizontal insights across multiple conversations, even from a small company perspective,
is incredible. So well, you'll start to see that soon
(34:11):
was contented. So the bigger, I guess for us, the
big vision also was contented is the ability to use
it for more personal conversations, for home life, to be
able to be putting in your parent teacher conversations so
you can share it with you know, a loved one
who couldn't make it all the way to doctor conversations.
We can see contented kind of being home to the
(34:32):
world's most important conversations, whether that's at home or you know,
in big contacts like the un You know, that's the dream.
Speaker 1 (34:40):
I'm sort of feeling it now where I sort of
want to record every conversation I have. You know, if
I'm at a public event, that's fine, but because I
want to get these this context, and I find that
when I'm having conversations, I'm just not able to listen
as and pick up the context as well as as
the something like arto which will remind me of things, well,
(35:02):
these points were made that you should maybe cover in
the story. So I guess culturally we're entering a place
where we're going to need to get more comfortable about
recording everything all the time.
Speaker 3 (35:14):
Yeah, I think, and I think it's probably quite a
long way from that. You know, people we find we
have to you know, coach them a bit of how
to ask for recording consent and how to not feel
awkward about it. And often it's about the other person,
you know, I would like to actually be able to
engage in this conversation with you, and if I write notes,
I can't and making it framing it. But I think
(35:34):
that that's definitely the future that we see is that
you know, all conversations, you know, are recorded and can
be used in amazing ways.
Speaker 4 (35:44):
So yeah, and that word consent is complicated, and for
us at the moment, our mobile app has a pop
up which, you know, while it is gimmicky, it's a
really great reminder to go, I have consent, click on it,
and it actually is just a nice one to ask
for permission. But the future of consent I think could
(36:04):
be more AI focused. It could be literally everyone saying
with their voice, I have consent before a meeting starts,
and that then you know, initiates recording or there's going
to be some really interesting ways of obtaining it. And
we're kind of researching this at the moment with some
great companies, but it's it is going to be a
different world, I think, especially for doctors. You know, we
(36:27):
often get a lot of g PEO ple in next
asking about I'm not sure about recording it, you know,
in recording our client conversations whatever. But actually on the
other side, we are hearing from the patients, you know, oh,
I've been recording our doctor conversations and then you asked
them not did you ask the for mession and they're
like no, you know, and so you've really got to
sort of yeah, it's going to be an interesting couple
(36:48):
of years around how we navigate this.
Speaker 1 (36:50):
Well, I've been doing exactly that with my dad who's
had cancer, and just so he and I can make
sense of what the specialists are saying. I've been hoarding
it and it's really helped. So I think healthcare is
a huge area of opportunity. There are patient portals give
us all of this jargon and all of this impenetrable
(37:10):
information about our health. But to be able to sit
down with a GP or a specialist and get that
in plane language summary and be able to refer to
that as is huge and many other industries as well.
So congratulations on bootstrapping your way to a really successful
AI company and all the best for the future. Thanks
so much for coming on the Business of Tech.
Speaker 3 (37:32):
Thanks so much.
Speaker 1 (37:38):
That's it for this week's episode of the Business of Tech.
A huge thank you to Lucypink and Hannah Hardy Jones
for sharing their story from solo founders to building Contented
AI into a platform trusted by over one hundred businesses worldwide.
And what really stood out to me, I think is
they're not just building tech for tech's sake or jumping
(37:59):
on the AI. They're focused on real world problems and
doing it from New Zealand, making AI accessible and genuinely
useful for everyone from journalists to mortgage brokers, and as
we heard, they're doing it with privacy, security and trust
at the core. If you want to learn more about
contented AI, what you're curious about AI could help your
(38:21):
business turn conversations into outcomes, check them out. And if
you enjoyed this episode, don't forget to subscribe, share and
leave us a review. It really helps us bring more
great Kiwi tech stories to your ears. We're on iHeartRadio, Apple, Spotify,
wherever you get your podcasts. Show notes are in the
podcast section at Businessdesk dot co dot Nz. Thanks so
(38:44):
much for tuning in. I'm Peter Griffin and I'll catch
you next time on the Business of Tech.
Cure and welcome to the Business of Tech powered by
two Degrees Business, where we dive into the latest trends
and stories shaping the world of technology and business here
in New Zealand and beyond. I'm Peter Griffin, and today
we're spotlighting a homegrown AI success story that's quietly making
waves on the global stage. We'll get into the podcast shortly,
(00:26):
but first a new and occasional feature I'm adding to
the podcast where I put a single question to someone,
someone who may have been a past guest on the show,
or maybe someone I think will have a really interesting
take on a tech related issue. This week's question goes
to Saab Johal, the former Massive University Associate professor in
(00:48):
mental health, author, tech commentator, and YouTuber. I had Sab
on the show over a year ago to talk about
the debut of Apple's Vision pro augmented reality head hit Cyber'
is a massive Apple watcher. Cyb really understands human psychology
and he's a real tech enthusiast, which led me to
(01:10):
ask him this question. When I've been increasingly pondering as
artificial intelligence proliferates, what part of your life should always
stay analog no matter how smart tech gets. Here's what
CYB had to say.
Speaker 2 (01:28):
For me, it's the slow, analogue moments that make space
for thought, like scribbling in a notebook or reading an
old paper encyclopedia with my kids and pausing to talk
about what we've just read. It might not be the
most up to day information, but it's good enough to
start a conversation, and that's the bit I care about,
the space to pause, reflect, and just muddle through together.
(01:54):
I live in a world full of tech. I film
with it, edit with it, and even use AI to
help me write sometimes, but not everything needs to be optimized.
In fact, some things shouldn't be. When I'm rising my hand,
for example, I'm not trying to be efficient. I'm trying
to feel what I think. That tiny bit of friction.
(02:16):
The slower pace makes it easier to notice what actually matters.
Because more and more research is telling us that it's
the dialogue between our left and right brains that's important.
The idea of having knowledge but not quite having the
language for it until we make space to allow the
relationship of language and deep knowledge held in the right
(02:39):
brain can eventually be verbalized by the left brain. It's
a slow groping in the dark gradual process, and at
the moment, all I see is AI models trying to
replicate left brain efficiency rather than a dialogue with our
more parallel processing summary of all things right brain. And
(03:03):
even outside of writing, sometimes I'd rather not have tech
jump in with the answer before I've even figured out
the question. There's value in the awkward pause, in not knowing,
in getting a little bit lost. So while I love
tech that makes life easier, I think there's a danger
when it makes things too easy, when we lose the
(03:25):
opportunity to engage, to struggle just enough to grow, to
connect in a more human way, not just with each other,
but with our own selves. So that's why I protect
the analog bits of my life, not because I'm nostalgic,
but because they keep me thinking, and they keep me present,
(03:46):
and they keep me connected with the richness of the
totality of me, and that to me is worth more
than perfect convenience.
Speaker 1 (03:56):
I really love that protect the analogue parts of your
life to keep you thinking and to keep you present.
Great advice from Cyberjohal. I'll put links to Cyber's substack
and his YouTube channel in the show notes. My guests
this week are Lucy Pink and Hannah Hardy Jones, the
dynamic duo behind Contented AI, a christ Church startup that's
(04:21):
reimagining how we capture and extract value from our conversations.
If you've ever left a meeting or an interview thinking
there's gold in there, but how do I actually use it?
This episode is for you. Lucy and Hannah's journey is
a pretty fascinating one. Neither started as a technical founder.
Hannah comes from an HR and mental health background, having
(04:44):
built the well being app Kite after her own personal journey,
while Lucy's path took her from ethical marketplaces to teaching
herself to code during lockdown. Together they've built Contented AI,
a platform that transforms everything from council meetings to client
calls into actionable insights, tailored outputs, and even content ready
(05:07):
for LinkedIn. On the face of it, this sounds a
little bit like you services like Otter, even the transcriptions
available in Zoom and teams services like Fireflies as well,
But Contented has gone much much deeper here to deliver
real insights from interview transcripts or recordings of meetings. We'll
(05:27):
talk about how Lucy and Hannah met at the Ministry
of Awesome's Coffee and Jam event what it's like bootstrapping
an AI company and ar Tairoa, and why they believe
the future of work is all about making every conversation count.
Plus we'll dig into how Contented AI is already helping
legal firms, journalists, and even EWI organizations get more from
(05:51):
their words securely, accurately and with a uniquely Keiwi approach.
Lucy and Hannah were both keynote speakers at Electrify our
tairo last week here in Wellington, a great conference centered
on women founders. I got along to a few sessions
and it really was a top notch event. I'd encourage
you to go next year. So let's get into it.
(06:13):
Here's the co founders behind up and coming AI startup
Contented AI. Hannah and Lucy. Welcome to the business of tech.
(06:36):
How are you both doing good?
Speaker 3 (06:38):
Really well?
Speaker 1 (06:38):
Thanks? So I've heard just recently about Contented AI, and
I'm on a mission to showcase some of the AI
startups that are coming out of New Zealand. I get
the feeling that we're a little bit slow, really too,
taking all of these great large language models and then
turning them into businesses, maybe slower than Australia, but this
(06:58):
year in particular, I'm seeing a lot of great companies
as a launch coming up this week for yet another
one in Wellington, So it's starting to happen. The pair
of you really got together. What was it in twenty
twenty three? The content had launched in April twenty twenty three, which,
when you think about it, wasn't that long after the
debut of Chat GPT, which changed the game when it
(07:21):
comes to generative AI. Take us back to the origin story,
after two of you meeting and having done quite a
bit in sort of business, but not necessarily as technical founders.
Speaker 3 (07:32):
Yeah, so we met at the Ministry of Awesome. We
actually a few years prior to starting Contented. We were
brought together as we're both speaking at an event called
Coffee and Jam, which was just showcasing early startups and
their ideas. We were both starting in the sort of
Tiohaka incubator program and it was Yeah, it was just
(07:53):
amazing to meet each other here about what we were
doing with our startups, hear about the problems that we
were solving. We became really close over that time really
just supporting each other as solo founders, you know, like
just having that community and being able to bounce ideas
off each other. And we got to the point it
was really when chetchybt launched that we saw the power
(08:16):
of AI and how it could help our own startup.
So just being able to power up what we were doing,
you know, with this lack of time and resource and capital.
We had suddenly a tool that could really transform what
we were doing. And that's when we decided to come
together to create something to help you know, businesses and
(08:38):
people use this technology. So that was the start of
the journey.
Speaker 4 (08:42):
Really we basically were Chatchybt consultants, you know for a
few months, you know, and we were because it was,
you know, yourself, as a startup founder, like can't mentioned
you're trying to make the most out of anything you get,
and AI was one of them. And so we became
in credibly proficient with chatjibt so quickly because finally we
(09:04):
could create content, we could do research, we could create
LinkedIn posts all based on kind of using a chatbot.
And so when we became really good at it, family friends,
legal firms, schools were asking for our help because we
just with somebody and people that just dived in. What
(09:24):
we found very quickly was a it's good if you're
sort of an individual person and you know what good
looks like, and you can use AI in a great way.
You know how to prompt, you know what is false
and what is true. But when you're trying to roll
that out across an entire legal firm and you're trying
to get people to use CHATCHBT and teach a whole
variety of people, that's when it gets very difficult. And
(09:47):
so we paed back really with chatchept, didn't we because
we were like, actually, we don't actually know if we
love the interface, We don't know if we love the
technology just yet. And we kind of went back to
the drawing board and started to talk to the businesses
we were working with to go, actually, what is it
with your pain points? What is it around your business
that you're wanting to use AI for? Is it actually
(10:09):
a problem? And so even though we were AI consultants,
we hardly ever spoke about AI. We're kind of just
talking about problems. And then that's kind of when Contented
started to become a product. But it really took about
a year and a half of R and D to
get to this point, which is where we're at.
Speaker 1 (10:28):
Yeah, so we're going to get into exactly what content
it does, but really intrigue at this mix of skills
and backgrounds that you bring to Contented. You know, Hannah,
I think the Kite program I'd love to hear more
about that. You've got sort of quite a mental health
and well being sort of background, and then Lucy obviously
(10:48):
debt to Daddy. Interesting to hear about that. So quite
an eclectic mix of different types of businesses that you've
been involved and tell us the sort of the background
to your businesses you were in coming to Contented.
Speaker 3 (11:01):
Yeah, so I started the Kite program. I'd actually come
from an HR psychology background. I'd also really struggled from
a mental health perspective after having my first baby, So
it really changed kind of where I saw myself. And
so Kite was based on you know, tiny steps micro learning.
It was an app. It could be customized to different
customers and different you know eating disorders or you know,
(11:25):
workplace well being, and so that was my whole passion
and I built it like I can hand on heart
say now, like it was built on my own experience
and what I thought people needed, and I did not
enough user research, and I went barreling down this path
of I've got to build this app and it's going
to be a global sensation, you know. And I think
there's a lot of learnings from there. But going through
(11:48):
that process and kind of being I can sell really well,
but I don't think I had really spent the time
to understand the customer. And so Lucy will share more
about this, but you know, that's when our skills come
together really well, because everything that I don't have, Lucy
has and potentially there by way around. So that was
(12:09):
that was my journey with kit.
Speaker 4 (12:11):
Yeah, and I think and Hannah's being low key about
it because you know, the selling and the passion also
helps with landing amazing customers like you know, the National
History Museum in London, you know, being able. I think
me and Hannah really collecked because we are such doers,
like once we've got it in our head that this
is where we want to be and we see the impact,
(12:32):
there's no stopping it, you know. And Hannah's ability to
stretch her impact all the way over to London US
and rally some amazing companies is testament to her. I'm
the opposite in the sense that I loved talking to
everyday people, understanding what it looked like. And as a consumer,
I built kind of an ethical marketplace and built and
(12:56):
started to learn to code based on my own problem,
which was I wanted to know more about where products
were from and if they were ethical, and I spent
a lot of time on Reddit. I'd be talking to
one hundred users around what is it around an ethical
white T shirt? You know, what is ethical? What does
that mean? How do you buy it? Where do you
want to buy it? So I did the opposite, and I,
(13:17):
as a comfort zone, went to building a product and
hardly selling. You know, I just wanted to build this
beautiful product and had the assumption that if you did that,
people would come to you, which is completely the wrong
approach because I think you're nothing without sales or revenue.
That combined we kind of came together. But going back
to Dada Daddy, it was an amazing way for me
(13:39):
to learn about startups and but building a business. My
boss met. He was incredible because he was so passionate
about you know, accounts receivable, maybe not the most glamorous
topic that you saw everyday guy wanting to build some
tech in software and a solution around it and build
an incredible business. So I kind of got a front
row seat that looks like. So that kind of propelled
(14:02):
me into startup world and having the kind of motivation
to do my own thing.
Speaker 1 (14:07):
And I understand it was sort of in the depths
of COVID that you decided I'm going to sit down
and learn to code. What inspired that move and what
was it like sort of doing that at a time
when you might have been sort of a bit more
isolated from the sort of people who are going to
help you on that journey.
Speaker 4 (14:24):
Yeah, exactly. I was during COVID, and it was the
first time I actually had the brain time, and it
was in a privileged position of, you know, living with
my parents who basically were making the amazing dinners, and
I got to spend my nights and days finally building
the software that I couldn't stop talking about. If you
talk to me, if you talk to the team at
(14:45):
deada Jelly, all I talked about was on you in
this marketplace. So it was this kind of perfect stars
alignment moment. What I had to do was I watched
countless YouTube videos. I started to build, I started to
learn to code. Was driven by a problem. So I
think if you if you asked me to do like
a software engineering pay for at UNI, I would have
(15:07):
hated it. But because I was driven by building this
thing that I've always dreamt off, I managed to do it.
And I loved engineering and I loved software and it
was always something that I loved to do and for
that school, and so yeah, I think what I did
find was I hated bugs, I hated checking code. I
had no patience for it. So again Star's alignment. AI
(15:28):
comes along, and I could build quickly fastly, I could
build well, and I could use AI to do all
the stuff I really didn't want to do.
Speaker 1 (15:38):
So yeah, yeah, and you know, I've just built a
website with an AI agent called Replet. It took literally
a couple of minutes. There's a whole host of these
AI agents now, so it's absolutely changing the game in
terms of software development. But Hannah tell us about contented AI,
(16:00):
and you know, it's built around this idea that every
conversation can be turned into extraordinary outcomes. I think that's
how you describe it, and it very much comes down
to voice and conversations. And this is at the heart
of what I do talking to people, doing interviews and
then getting transcripts. I'm using tools like Otter and Fireflies
(16:20):
and even teams to make sense of all of these
conversations that I'm having and get contexts. So all of
these tools were sort of being infused with AI around
twenty twenty three. Tell us about this particular take you
wanted to have on conversations and extracting value from them.
Speaker 3 (16:39):
Yeah, so when we first started, we were doing lots
of different sort of mini projects. Some of them were
voice inputs, some of them were imaged, some of them
were data, and we found time and time again that
the most valuable input into these tools is voice data.
You know, a transcription of incredible words is so much
(17:00):
more meaningful than just some data or a few prompts.
And so we realized that it was conversation, not just meeting.
So a lot of the tools that you'll see will
be note takers. They're very focused on these sort of
transactional turning a meeting into some summaries. We wanted to
take this value of conversation and just really push that,
(17:20):
so we talk about wasted words. You know, in a business,
the amount of words that we say in a day
that are valuable that could actually have an outcome to them,
whether it's turned into content or you know, a proposal
or something for the team to share. You know, this
huge value to that. So that's where where we come
(17:41):
in is it's not about just a traditional business meeting
that needs an output. In our businesses that we work with,
they're using conversation from musings through to team meetings through
to a conference speaking session. You know that there's so
much richness across everything, and we like to see it
(18:03):
being you know, we talk about it sometimes being like
canvas for conversations. It's one conversation asset can turn into
so many different things, and that's what really excites us.
But that's also what excites our customers so much, is
just this world of opportunity from this one conversation.
Speaker 1 (18:20):
You're using some of the top large language models, you know,
presumably from open Ai and maybe Claude and others as well,
and they're really attuned to natural language processing and making
sense off conversations. But what process did you have to
go through actually adapting all of those to your specific needs.
Speaker 4 (18:42):
We were really fortunate that a couple of years ago
a man called Pedal the Fort came on to our
kind of doorstep. It was his last day in New
Zealand on holiday and he saw Contented the sign and thought,
what is this AI company? And it was really early
in the sort of age of AI. So he had
a coffee with me and Hannah which ended up being
kind of a four hour conversation, and Peter had worked
(19:05):
at Microsoft for a really long time and he really
understood our vision which Hannah just mentioned before, which is
seeing conversations being an incredibly rich data source that previously
without AI, was untapped, you know, and people were having
meetings without any traction or outcomes coming from it. So
we contented we're finally seeing that. But to be able
(19:25):
to earn the right to kind of work with businesses,
to do that, you have to be accurate, You have
to have safeguards, you have to work with great models,
you have to have great kind of hallutionin hallucination prompting.
You have to be able to provide all of these
frameworks and the person or the industry to help us
build out. With journalists, we worked with journalists over in
(19:46):
the US to build the kind of first version of Contented,
which was to take kind of five hour council meetings
and turn them into news stories. Because in the US
at the moment, you're seeing a kind of decrease in
publications news agencies. So you've got incredible individuals who are
kind of taking that on. And so we have a
(20:06):
large customer base in the US that users contented to
turn council meetings into news to keep their communities informed.
But in order to do that, you have to be accurate.
So Contented today was built off the back of challenging
circumstances and the sense that I would spend a summer
building and creating incredible frameworks around these llms and choosing
(20:31):
the right llms, and at that stage, every week there
was a new model, and every model would let me
down technically, you know, and I'd still have to build
huge prompt frameworks around these models to make sure that
they were accurate. They were long, and they were good,
good writing. And one of our kind of publications was
the Palm Springs Post, and they had worked with some
(20:54):
incredible publications. They've come from amazing backgrounds, and so his
kind of his perception of writing was incredibly high, so
we had to make sure we were building some great outputs.
So yeah, so we've been challenged across all of our
building and I think that's why people love us is
because our level of accuracy and outputs is next level.
Speaker 1 (21:17):
Yeah, that's you know, it just resonates so much with me.
Obviously in terms of democracy itself, you know, newsrooms are shrinking,
We don't have enough journalists. You know, Luckily there's some
funding through the Democracy Public Journalism funding from the government
that is continuing to allow people to go and cover
(21:37):
council and local court. But there's just too much information
and not enough people to sift through it. So if
you can record all of that and actually make sense
of it in a way that's useful for the needs
of democracy and journalists. So, Hannah, how does that sort
of concept apply to other types of businesses that you
work with? It seems like what mind mapping and business
(21:59):
plan So turning all of those conversations and transcripts actually
into output that's useful for a business trying to decide
where it's going.
Speaker 3 (22:08):
Yeah, so we we're identified in the hub of contented
is sort of some standard outputs that everyone can create,
so a SWAT analysis, a summary, a risk matrix, human
centered OUTPUTSLACK, people's struggles and motivation. So those are across
all of the businesses that we work with. The benefit
is that each business also gets to have their own
(22:28):
custom outputs that we have developed alongside the industry. So
within finance, and within law and within health. So you know,
these buttons that people can create that are very specific
to the conversations they're having in that industry, and we
find that works incredibly well. It makes contented, relatable and
accessible to everyone, and then each kind of customer base
(22:50):
can also have best practice from their industry and kind
of you know, it's almost like having an incredible consultant
coming alongside your conversations and turning it into things. But
they get to click a button, and that's really important.
And I think from a you know, even working with
you know, if someone's trying to get an output from
say chat TOBT, the hard thing is is you're prompting
(23:10):
to the level of you know, you have to put
so much effort into that. And so we make this
accessible that anybody in any industry can literally click a
button and get this absolutely high level output every time,
and there's a lot of comfort in that for people too,
because they don't want to have to do all that
hard yards with a chatbot.
Speaker 1 (23:30):
Yeah, and look, you said earlier that you don't really
talk about the AI aspect of it. You're trying to
make it really simple and seamless. So do you adapt
the app for different industries or does everyone get the
same dashboard to look at? We adapt?
Speaker 4 (23:47):
So a good example might be if you're a mortgage
broker or an insurance firm. They're a really good example
because there's so many requirements and needs and outputs from
just one conversation. So let's say it's discovery conversation with
a couple who are looking to buy their first home.
You know they would create and contented their perfect proposal
(24:08):
back to them to say this is what I'm hearing.
Within the same vein, they've worked with us to create
the mortgage application form and the outputs needed for that.
So from just that twenty minute conversation, they're creating the
form that they will then send to the bank. They're
also creating a compliance checklist, so they need to be
able to show that they've provided the right advice. They've
(24:28):
made sure that they're not a vulnerable client, so they
need to show that they can tick that off. They've
asked the right questions, so they create that and then actually,
because they're asking the right thing and they're providing advice
and on that day they're finding great advice, they actually
then go into our marketing module and they create a
LinkedIn post or a LinkedIn blog to say, hey, if
(24:49):
you're a first home buyer and you're about to go
to auction, these are the things you need to prep for.
And then potentially if they're looking to get in a
new team member or they're wanting to train another advisor,
they could then go and create a cheat sheet to go, hey,
these are the questions I asked, and actually these are
the questions I should have asked too, and create some
internal training so that kind of if you can visualize that,
(25:13):
it's one conversation, like Hannah mentioned before, sweated into so
many amazing assets, and I think for advisors they shouldn't
have to go into LinkedIn to go, shit, you know
what am I going to write about today? And what
does that look like? They're actually they've got the expertise
and advice there in these conversations, and that's what they
should tap into.
Speaker 1 (25:33):
You talk about things like you're creating LinkedIn posts and
that sort of content. A lot of people will probably
be doing that in chat, GPT or maybe even Microsoft
Copilot if they've got a subscription. But we're seeing services
like Contented, which is doing all of that for you.
So how do you position yourselves in terms of saying
to customers you can actually do all of this. You
(25:54):
don't need this proliferation of subscriptions, you can do it
all through our PlantForm. And related to that, how do
you avoid just being seen as a feature rather than
a business a feature that potentially is going to get
built into one of these big platforms like Otter in future.
How do you position yourself so that it's worth having
(26:15):
a subscription to Contented instead of you know, some of
these other big sort of platforms that have emerged.
Speaker 3 (26:21):
Yeah, I mean the big things for us is our
transcription is better than anything on the market. If we
can get a potential customer to experience Contented, that's it.
They don't need any other convincing because it's so clearly obvious,
you know, And it's all those things that in person meetings,
we thrive and you know, being able to just use
your phone and have that being able to analyze really
(26:42):
quickly with noise and accents today you know, multiple speakers,
So particularly in New Zealand, obviously we've got a lot
of EWE lead EWE owned organizations that love us because
of how we treat today a Maori and so there's
that side of it, and then there's obviously just the
unbelievable quality of output which is just incomparable, you know,
(27:05):
And that's a huge part of it. And I think
because you can have it rolled out across a whole organization,
and we're working with some really large New Zealand businesses
because it taps into everybody's roles, you know, and everybody's conversations.
It's so easy to roll that out and it be
solidified and everything, whereas most other tools are just pockets,
(27:27):
you know, and some people love them, some people don't.
So that's where we're really leaning into the fact that
it's just so easy to adopt it too because it
works so.
Speaker 1 (27:35):
Well, right and Lessie, it's clearly very useful for strategic conversations,
risk management, that sort of thing needs are quite sensitive conversation,
So how do you deal with that putting your customers
sort of minds at ease that this stuff is going
to be private. It's going to be it's sensitive information
(27:58):
that it's you know, so how do you store it
and make sure that all of those conversations actually stay private?
But you get these great outputs from them, and I guess.
Speaker 4 (28:06):
We work with the company. So for example, if you
are a high needs customer, you might want to do
things like PII reduction, which basically means you can redact
names before they even hop into an AI model. So
we offer a menu of ways to customize how you
know private, you want these conversations to be honest. We
(28:27):
take our role really really responsibly. So data, I guess
before the age of AI, you know, people kind of
knew what companies did with it, but you know, they
kind of just let it go and happen. But now
you've got these questions like is this company training our
data on AI? And tech firms are having to come
to the fore to kind of deal with this situation
(28:50):
where now a lot of users want to know what's
happening with their data. So as a new company, we
get to work in a world that accommodates this. We
know that the local pizzeria wants to know that their
data is going to be stored in New Zealand or
if closely you know, Australia. They want to be able
to have that, which is before, I guess before they
(29:12):
didn't even have that opportunity. So we offer that to
our customers in terms of where that data is stored
and what that looks like in terms of you know,
risk conversations or sensitive conversations. The outputs we create are
based with their customer. So for example, if it is
a risk matrix, we work with them to go what
actually is risk? How do you infer risk?
Speaker 3 (29:32):
What is risky?
Speaker 4 (29:34):
And so actually every output is kind of pretty customized
to that customer because risk might look a lot different
to another business. And so I think that's where you know,
chatchept goes wrong because if you put in their conversations
and make me a risk matrix, you're you're asking chat
chept to quantify that risk and you don't know where
(29:54):
that's from. So for us, it's a lot around personalization
and using AI to help with that.
Speaker 1 (30:00):
You've got I think over one hundred customers now and
a lot of international customers. How did you go international
as a small New Zealand AI startup based in christ Church.
What was your sort of key drivers of your international adoption.
Did you sort of what goes straight to newsrooms first
and target them or was there a particular segment that
you went after initially.
Speaker 3 (30:21):
Our whole go to market currently, honestly is word of mouth.
You know. We got an amazing sports publishing company in
London as a customer and they had just seen someone
talking about it, you know, online on Twitter from America.
You know, like this is the level of you know,
we'll speak at a conference or we'll partner with a
(30:41):
conference to create like a version of contented for them.
It spreads so fast and so we haven't targeted necessarily
actual you know, geographical regions. It's just been this organic focus,
which is a really exciting part for us into this
next phase, which is when we can target We do
have the capital to be able to really launch you
(31:03):
know into a particular region or city, we can really
nail that. But yeah, it's been an organic process.
Speaker 1 (31:10):
Wow, that's great, And where you at on your sort
of capital journey you're obviously you know, generating revenue now,
which is fantastic. Have you raised money or are you
looking to raise more money?
Speaker 3 (31:23):
We're soon.
Speaker 4 (31:24):
Yeah, we're bootstrapped and proud of it, and we're stoked
because it meant that we've built a business on our
own terms, you know, and we've felt what building a
business looks like, and we know that we can take
a risk and a risk can pay off because we've
got our own capital behind it and we've got our
own team. So we've been able to do this, you know,
(31:44):
for across the last couple of years, and what we're
really excited for, like I mentioned, is to be able
to actually put a bit of capital behind this. So
we will be looking to kind of start the conversations
around an investment across the next couple of months, just
to see if we can find some great investors who
kind of understand our vision, who want to jump on
(32:04):
board and to help us with this kind of next
stage of growth, which will be exciting.
Speaker 1 (32:11):
Okay, fantastic. Well, hopefully someone's listening who really likes the
sound of this business and it has some money to invest.
But just finally, for both of you, where do you
see Contented going and in terms of this sort of
technology around voice and conversations. For instance, I see the
game changer that's coming in it's sort of possible now,
(32:33):
but it's a bit clunky having these new conversations but
then combining that with all of your institutional data and
past conversations to make sense of where thinking has gone
in an organization. So it's you're not just having the
same conversation again and again as new people come into
the organization. You're retaining that institutional knowledge and supplementing it
(32:54):
with new conversations. And I'd love to see more in
that space, but interest in your views on the features
that are coming or that you know you really would
love to see in Contented.
Speaker 4 (33:06):
Yeah, and we're spearheading at the moment, so you can
imagine now, customers trust us with their sensitive conversations, and
trust is at the center of what we do. So
the vision of Contented will always be around trust and security.
And with that trust, it means that we've aren't the
right to be able to build incredible features like horizontal
(33:27):
insights like you just said. You know, you've got a
council that's put through all of their council conversations, that
council meetings imagine if you could go back and create
some insights around, Okay, what we're we talking about? You know,
what were the problems? Where do we keep on, you know,
talking about that same problem. How can we do a
council meeting better? Who is roadblocking? What does that look like?
(33:49):
We've spent the last couple of years, you know, creating
an LTP. Are we getting anyway close to this? You know,
this is the LTP. This is six months of council meetings?
What does this look like? So being able to have
horizontal insights across multiple conversations, even from a small company perspective,
is incredible. So well, you'll start to see that soon
(34:11):
was contented. So the bigger, I guess for us, the
big vision also was contented is the ability to use
it for more personal conversations, for home life, to be
able to be putting in your parent teacher conversations so
you can share it with you know, a loved one
who couldn't make it all the way to doctor conversations.
We can see contented kind of being home to the
(34:32):
world's most important conversations, whether that's at home or you know,
in big contacts like the un You know, that's the dream.
Speaker 1 (34:40):
I'm sort of feeling it now where I sort of
want to record every conversation I have. You know, if
I'm at a public event, that's fine, but because I
want to get these this context, and I find that
when I'm having conversations, I'm just not able to listen
as and pick up the context as well as as
the something like arto which will remind me of things, well,
(35:02):
these points were made that you should maybe cover in
the story. So I guess culturally we're entering a place
where we're going to need to get more comfortable about
recording everything all the time.
Speaker 3 (35:14):
Yeah, I think, and I think it's probably quite a
long way from that. You know, people we find we
have to you know, coach them a bit of how
to ask for recording consent and how to not feel
awkward about it. And often it's about the other person,
you know, I would like to actually be able to
engage in this conversation with you, and if I write notes,
I can't and making it framing it. But I think
(35:34):
that that's definitely the future that we see is that
you know, all conversations, you know, are recorded and can
be used in amazing ways.
Speaker 4 (35:44):
So yeah, and that word consent is complicated, and for
us at the moment, our mobile app has a pop
up which, you know, while it is gimmicky, it's a
really great reminder to go, I have consent, click on it,
and it actually is just a nice one to ask
for permission. But the future of consent I think could
(36:04):
be more AI focused. It could be literally everyone saying
with their voice, I have consent before a meeting starts,
and that then you know, initiates recording or there's going
to be some really interesting ways of obtaining it. And
we're kind of researching this at the moment with some
great companies, but it's it is going to be a
different world, I think, especially for doctors. You know, we
(36:27):
often get a lot of g PEO ple in next
asking about I'm not sure about recording it, you know,
in recording our client conversations whatever. But actually on the
other side, we are hearing from the patients, you know, oh,
I've been recording our doctor conversations and then you asked
them not did you ask the for mession and they're
like no, you know, and so you've really got to
sort of yeah, it's going to be an interesting couple
(36:48):
of years around how we navigate this.
Speaker 1 (36:50):
Well, I've been doing exactly that with my dad who's
had cancer, and just so he and I can make
sense of what the specialists are saying. I've been hoarding
it and it's really helped. So I think healthcare is
a huge area of opportunity. There are patient portals give
us all of this jargon and all of this impenetrable
(37:10):
information about our health. But to be able to sit
down with a GP or a specialist and get that
in plane language summary and be able to refer to
that as is huge and many other industries as well.
So congratulations on bootstrapping your way to a really successful
AI company and all the best for the future. Thanks
so much for coming on the Business of Tech.
Speaker 3 (37:32):
Thanks so much.
Speaker 1 (37:38):
That's it for this week's episode of the Business of Tech.
A huge thank you to Lucypink and Hannah Hardy Jones
for sharing their story from solo founders to building Contented
AI into a platform trusted by over one hundred businesses worldwide.
And what really stood out to me, I think is
they're not just building tech for tech's sake or jumping
(37:59):
on the AI. They're focused on real world problems and
doing it from New Zealand, making AI accessible and genuinely
useful for everyone from journalists to mortgage brokers, and as
we heard, they're doing it with privacy, security and trust
at the core. If you want to learn more about
contented AI, what you're curious about AI could help your
(38:21):
business turn conversations into outcomes, check them out. And if
you enjoyed this episode, don't forget to subscribe, share and
leave us a review. It really helps us bring more
great Kiwi tech stories to your ears. We're on iHeartRadio, Apple, Spotify,
wherever you get your podcasts. Show notes are in the
podcast section at Businessdesk dot co dot Nz. Thanks so
(38:44):
much for tuning in. I'm Peter Griffin and I'll catch
you next time on the Business of Tech.
Popular Podcasts
United States of Kennedy
United States of Kennedy is a podcast about our cultural fascination with the Kennedy dynasty. Every week, hosts Lyra Smith and George Civeris go into one aspect of the Kennedy story.
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Follow now to get the latest episodes of Dateline NBC completely free, or subscribe to Dateline Premium for ad-free listening and exclusive bonus content: DatelinePremium.com
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.