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Thank you John.

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Mosaic is workforce optimization and
intelligence platform,

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also what we call AI resource planning and

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people analytics which make up
the core components of that.

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Our growth over the last year and
just over a year and

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a half has been pretty remarkable.

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We've really caught our stride and
a lot of that aided by the pandemic

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of course and
market forces that we're experiencing.

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We're now at 2.6 million in ARR as
of March 1, and we highlight here

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that growth rate that we've maintained
over that period of over 30%.

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The core problem that we're solving,
and that John touched on there is that,

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it's 2022.

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And all organizations including very,
very large organizations are doing their

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resource planning, a core business
function of theirs, on spreadsheets.

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And they've prepared and created over the
last two or three decades, these elaborate

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spreadsheets that give them visibility
into what people are working on and

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help give them an assessment of
the workload of the organization.

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But it's very disjointed and detached
from the other aspects of the business.

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Effectively, executives and
really everyone above the project manager

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there of course in the day to day
tools on the project management side.

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But the executives and everyone else
don't have the visibility into what

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people are working on or the workload.

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And they don't know when to hire or

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what role they would need to
hire from a workload standpoint.

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The good thing about the product that
we're building and what really makes us

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special is that we have a motivation for
that workforce visibility and

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the information and
the analytics on the workforce.

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That makes enterprises want to
connect their current tools to get

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the information into our system and
aggregate it all together.

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Some of those tools HR, Payroll, sales,
data lakes, communication tools like

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slack and email of course, project
management tools like Asana, Monday,

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among others, calendars and their ERP
which of course has a wealth of data.

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One of the core functions that we serve
to do is to help them visualize their

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workforce.

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Understand what people are working on,
their workload,

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as well as how it's changing,
given changes in the business and

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demand on different aspects,
departments within offices,

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and of course roles so
that they will know hiring information.

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We are an out-of-the box BI solution as
we like to put it, but specifically for

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workforce analytics as opposed to
a Tableau or Microsoft Power BI,

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where you can do anything and
pull up any chart and create the charts.

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By out-of-the-box we mean these
are pre-prepared reports and

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widgets, they're thousands of hours,
have gone into the design.

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And it's a real curated experience
where people can look at them and

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immediately understand
what they're saying.

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And they're specifically designed to be
filtered in different ways that relate to

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that report.

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And even beyond that,
a report specific to industries or

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to a specific industry I should say.

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We then with our ML and AI layer,
we give them insights, looking at all

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of the data from across, any of
the platforms that they've plugged in.

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One of the core things that we do is
give them insight into the workload,

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and forecasting that out for
the next quarter.

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That of course gives them
a heads up on hiring demands,

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again, within departments,
regions, offices and roles.

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So we might be able to offer them
that they need to hire a couple

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project managers in a specific
office in the next 60 days.

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And they're going to work on these
projects based upon the data we

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have in the system.

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And ultimately, we're helping them
understand their workforce and

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accurately plan the headcount.

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We do work charts within
the system automatically,

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really providing suggestions
to build those out.

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And then also collaboration
based organization charts

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around who works with who and
how much effectively.

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Two core things that we do,
improving efficiency and performance with

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AI by managing the organization
with the ML and I work that we do.

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And by that we're tweaking things,
offering alternate schedules,

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offering different people to work on it
if there's a short fall on a project.

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And it's gonna be two months delayed,

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you can immediately go to Mosaic and
find out 20 engineers that you need

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to get that project completed on
time from different departments.

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It's all done by simply
adding some filters,

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layered in with the machine
learning work that we do.

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Ultimately you exist, and
that function to increase engagement and

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retention by balancing the workload for
individuals and preventing burnout.

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One of the higher callings of what
we do is that burnout prevention

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obviously the pandemic has resulted
in a situation where already poor

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visibility into how much people
were working has gotten even worse.

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And you'll have people in
one room working 12, 14,

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15 hours and then people in
the next room doing nothing and

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no one is at all aware
of what's happening.

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So, we've got a great ROI
that we offer folks and

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this is supported by the numbers that
we see in companies that build time and

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closely track time and build it of course,
where we're increasing their

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profit by a million dollars or
more per year for every 100 people.

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And this number might sound like
a staggering number, a big number there,

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of course, but it only highlights
the inefficiency that you see within

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the current process
that's on spreadsheets.

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And exporting and
the energy that's spent and

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the sheer number of people that it takes
to put that information together on

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an ongoing basis, Our sales funnel,

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one of the things we highlight is that
we have made our first million dollars

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on just outbound cold calling where
people don't know who we were.

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And by the end of the call,
they were booking a demo and

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less than two weeks later they were
buying the product in early days.

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And we took that as a really
strong indicator for

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the pain point that we're fulfilling here.

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Our outbound sales motion involves,
of course there's calls, emails,

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pay per click channels or

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paid channels as well as webinars which
we've been highly effective with.

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We did a couple of webinars that
one in particular had 450 signups,

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over 200 attendees, and
we booked 92 demos on the back of it.

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So, it was surprising even for our
marketing folks who had been doing demos

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their entire career will do on average,
we'll book 50 to 60 demos.

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We've got a great show rate of about 80%,

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30% close rate on those demos
lifetime ,and that metric is

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held strong as we've expanded
into over 20 verticals now.

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Lifetime conversion rate from
the 30 day trial that we offer,

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is 85% and
interestingly enough in q4 was 95%.

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Again, just another indicator of
the offering and the improvements, and

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the great strides we are making
on the product side as well.

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We have over 350 paid
companies on the platform.

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And as we like to say, in this new
hybrid world where work can't be seen,

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Mosaic is a necessity.

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And this customer quote highlights that,
there were enabling those conversations

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around strategy in business operations
across all levels of the office, which

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has never been possible before without
the visualizations that we provide.

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It's important to highlight some people
aren't familiar with resource planning.

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This, again is not something we invented,
there are hundreds of incumbent products,

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it's really we're about that next gen
version of it, and what that looks like.

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But some of the industries we list
here for resource planning that

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are currently doing them on
spreadsheets and these outdated tools.

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And some $35 billion Tam in
the US market across them, and

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we're going after, and I should say
we're going after because we've

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already expanded beyond our
initial time building verticals.

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But they're key to us because
they track time the most closely,

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of course, and so that's very valuable
to us from machine learning and

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algorithm development standpoint.

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Some of our traction that
we're highlighting here,

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some of these I touched on but
are down now 50%.

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We're just highlighting that
we've got great usage and

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people are really using the product
how we would expect them to use.

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People who are heavily
involved in the staffing and

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management of what people are working
on are in their daily executives or

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in their weekly checking in on reports and
getting information about the business.

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And we even go down to the project
managers are involved in providing

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the information as well as the individual
contributors who will receive

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the information on what their upcoming
projects that they'll be working on,

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and engaging in discussions
around within the platform.

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The interesting note that we like to
highlight too is that the company

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is not converting on the platform,
half of those are not right now, so

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a really strong metric for
us on that side.

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Pipeline here has not been updated,
it's now stands at 18 million,

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it's growing rather rapidly as we've
been going up market to enterprises.

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And about 75% of that pipeline
are enterprise companies which we

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define currently as over 100.

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But we're in late stage with companies
in the mid to high thousands,

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6,000 and 12,000.

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We've got a great land and

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expand opportunity through
our current sales flow,

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which has been to just sell into smaller
teams within the larger organization.

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So we have a couple that
are 100 within 2000, and

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several that are 100 within
high hundreds as well.

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We see our process is repeatable and

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scalable as I've highlighted early on the
sales motion that we've been following.

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Marketing has also been strong,
38% discovery call the demo,

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47% of those marketing leads
are leading to a close, and

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we've had a great row as
on that marketing spend.

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And we're really excited to as we
raise our series A now to lean in and

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see where that can take us.

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Founding team myself my background
on of course Nima Tayebi,

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we met over four years ago now through
a shared friend in the industry.

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And he had come from
a Microsoft background and

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just has built an incredible amount of
the product in early days single-handedly.

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Nick Curcio joined us two and a half years
ago to really build out the business

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side of the organization,
as we have built this great product and

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it was time to build
an organization around it.

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And he comes out of a finance background,
ten years on wall street,

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and then a similar, ML AI,
startup, in the retail space.

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Thank you for your time.