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Leni (fka RealSage) - Overview Memo



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LENI (FKA REALSAGE) - OVERVIEW MEMO



Introduction
Problem
Solution
Product Overview
Team
Traction
Business Model
Market & Customers
Competitive Landscape
Go to Market
Frequently Asked Questions (FAQs)
Contact



INTRODUCTION


We are on a mission to revolutionize the way the real estate industry makes
decisions.

Decision-making in real estate relies on notoriously fragmented data residing on
multiple systems and tools that don’t talk to each other. These data sets are
often managed on Excel spreadsheets by a fleet of analysts to empower
multi-billion dollar decisions without much foresight. This process leaves asset
owners and operators vulnerable to cost overruns, missed IRR targets, and budget
shortfalls, hampering long-term portfolio returns.

In larger enterprises, this problem is exacerbated as 28% of management time is
spent on meetings, trying to gather information from various teams and
portfolios to make important decisions, leading to annual losses of over $5
billion for some top enterprises across North America.

Leni solves this problem by providing a decision support platform that
seamlessly combines siloed internal and external data sets to generate AI-driven
insights for better decision-making.

The system leverages data across the portfolio to enable on-demand
visualization, analysis, and predictive reporting for real estate owners and
operators, helping them generate better returns and have a clearer foresight on
portfolio performance.

We diverge from most BI and dashboarding tools by offering unique Al frameworks
for data ingestion, analysis, and benchmarking across diverse internal &
external data sets. Our technology navigates directly to valuable predictive
insights and facilitates conversation-based data discovery, providing our users
with a competitive advantage their teams are looking for in the current market.

Our vision is to revolutionize real estate decision-making by 2028! We aim to
become a market leader, eradicating inefficient and Excel-based processes by
working with 5,000 industry owners/operators. This approach anticipates gaining
significant market share within the enterprise segment, onboarding 20M+ units
across 60K buildings, and influencing 50K decision-makers in North America. This
also get us to $100MM in revenue by 2028.

This niche is the starting point of our journey. Our long-term vision is to
extend our reach into sectors that are not just ancillary but also deeply
intertwined with rental management data. This includes the trillion-dollar
markets of insurance, banking, and RE transactions. These sectors collectively
represent over $12 billion opportunity, opening up vast avenues for us to grow
and expand.

Prominent multifamily players like Oxford, Concert, CAPREIT, InterRent REIT, and
Cogir Real Estate have already signed up for a portion of their portfolios on
our platform and are growing their investments with us. We have a sales pipeline
of over $735,000 with the likes of CWS Apartments to help them improve their
decision-making and reporting processes.

In the last eight months, the platform has seen 30x growth in adoption across
50,000+ units and 300+ buildings in six major cities across Canada and the US.

Know more about our traction here, and check out the FAQs if you have questions.




PROBLEM


Over 47 million rental assets across North America comprise one of the biggest
asset classes for many institutional and private equity investors worldwide.
Yet, this asset class, holding over 43 trillion dollars of assets, is still
reported and managed using scattered data across multiple channels and layers of
operations, pulled together by analysts to barely meet quarterly reporting
requirements for asset managers and owners. This problem of manual, low
fidelity, and backward-looking reporting and decision-making structure renders
asset owners and managers vulnerable to cost overruns, budget overruns, and lost
deals, hampering long-term returns.

These inefficiencies across asset lifecycles cost more than $5.5 billion yearly
to some top enterprise rental managers and investors in North America.

Our mission is to address a critical, industry-wide problem: the slow, manual,
and inefficient decision-making process currently crippling the real estate
industry.

The key challenges are as follows:

1. Siloed Data: Information in real estate operations is often scattered across
different teams, departments, and external sources. This fragmentation creates
significant inefficiencies and a lack of transparency that slows down
decision-making. 2. Complex and Unstructured Data: The vast and complex data
generated by real estate operations is challenging to manage and analyze using
conventional tools, leading to a slower decision-making process. 3.
Over-Reliance on Manual Processes and Outdated Technology: Decisions are often
based on data manually pulled together by a large team of analysts using Excel
spreadsheets. This approach is resource-intensive and prone to errors and
delays, further slowing down decision-making. Also, the heavy reliance on Excel,
which wasn't designed to handle the volume and complexity of data in large real
estate operations, often leads to system crashes, and spreadsheets on the cloud
are slow to collaborate efficiently.  4. Inefficient Use of Management Time: In
larger enterprises, approximately 28% of management time is spent in meetings
attempting to gather information from various teams and portfolios to make
critical decisions. This inefficient use of time can lead to significant losses.
5. Cost Overruns and Budget Shortfalls: The current state of data management
leaves real estate asset owners and operators vulnerable to cost overruns and
budget shortfalls, negatively impacting long-term portfolio returns.

Zain, Gaurav, and I noticed this problem of inefficient decision-making
processes while working for important North American asset owners and operators
in asset management and private equity teams. We conducted preliminary processes
to fix issues with rental teams and organized data from different
software/systems to make frequent reports that helped with decision-making. This
improved asset returns by 30%.

This initial success, understanding of the pain point at the functional level,
and discussions with hundreds of industry veterans helped us create what we have
at Leni.

Learn more about our mission and decision-making in real estate here.




SOLUTION


Leni is a decision-making platform for real estate owners and operators. We use
data science and AI to help real estate asset managers make fast and accurate
decisions regarding the acquisition and management of asset portfolios.

Use cases include rental go-to-market and renewal rental offer price decisions,
budgeting reallocation decisions, CAPEX investment-related decisions, leasing &
marketing management, and refinancing.

For instance, for actively reallocating your budgets to reach your NOI
performance targets for the quarter, you would need both internal and external
data around areas like marketing spend and channel performance, and our system
not only allows you to view all these various KPIs in realtime across portfolios
but also auto flags and suggests reallocation actions that can get you closer to
your destination/targets.

ALT

We bring our clients from hindsight to foresight in the sector, which is
essential to provide them with a competitive advantage in the market. Having
foresight in real estate is the holy grail of decision-making.

ALT

Over time, the system will recognize changes in these sets and use unique
deterministic AI models to provide predictive and prescriptive insights. These
point out investment opportunities, benchmark changes, revenue improvements, or
cost savings based on the manager's preferences. Essentially simplifying and
accelerating the entire decision-making process, making it 10x more efficient
for the organization.

Leni eliminates data across functional and technological silos and enables
seamless conversations with your data 24/7. You can now know your latest numbers
at all times, whether you need them during dinner with a banker or right before
your quarterly meeting; we have got you covered. Experience the power of
advanced language models and proprietary database query response mechanisms to
get your answers in plain English.

ALT


ALT

Seamless access to data and foresight-driven decision-making help capital
allocators close more deals, asset managers manage bigger portfolios, and asset
managers generate more returns.

A few empirical benefits for our clients are below:

ALT




PRODUCT OVERVIEW


At Leni, we aimed to create products with two goals:

Design proprietary data models and AI-based systems to provide actionable
predictive insights on processes and asset performance

Help multifamily teams transition easily to more data-driven decision-making

We exist to empower multifamily teams across the world with the best tools to
make data-driven decisions.

That's why our first product version comes with a range of integrations that
help rental managers start swiftly from their existing systems.

ALT

Our clients love what we have created. We are excited to deliver a robust
product roadmap driven by client feedback that will enable rental managers to
look deeper into their data across more use cases in their business.




TEAM


Our team combines their deep experience in real estate (JLL, Cushman &
Wakefield, and Greybook) alongside their experience in banking and technology
(Goldman Sachs, RBC & Zomato) and applies it to the world of Leni.


ALT

Arunabh Dastidar, Co-founder & CEO

Gaurav Madani, Co-founder & CRO

Zain Nathoo, Co-founder & CIO/COO

Leon Nsengi, Tech Lead

In addition to the stellar team, some of the top people in the industry support
us. Here are some more details on our team, mentors & advisors:

ALT

If you are interested in learning more, you can also visit the company page on
our website.




TRACTION


We, as a team, have made significant progress toward our vision.

We did our commercial launch 11 months ago and landed our first enterprise
client in Oct 2022. Since then, we have seen a significant adoption, and in the
last quarter months, we added more clients to Leni than in our first two
quarters combined.

We have landed four top enterprise clients in the last four months. Our current
users include the likes of InterRent REIT, CAPREIT, and Concert, using our
product across 50,000+ doors (300 buildings) across six major cities and 30+
economic centers across Canada and the US.

Some other key metrics are:

Revenue Dynamics: $395K ARR, stellar 100%+ QoQ growth for two straight quarters.

Growth: Product adopted by 300+ buildings since Q2 2022 beta launch, hired top
sales talent from Zillow/Zumper.

Quick Ratio: A high User Quick Ratio of 10.0 indicates sustainable growth.

Experienced Founders: Ivy League, Ex-RBC, Goldman Sachs, Private equity, 2x
founders.

Client Portfolio: 13 enterprise clients, including Oxford Properties (OMERS),
Sunrex, and GreySpring Apartments (Marlin Spring).

Sales Success: A promising $700K sales pipeline within twelve months of
commercial launch, targeting enterprise owners/operators with 6k+ units, 80%
margins, and average $31K annual contracts (ACV).

Retention Rate: 140% of the revenue.

Notable pre-seed investors: Backed by VCs in Silicon Valley and Texas
like NAR-SCV (Docusign Investors, owners of Realtor.com), Golden Section, and
Plug & Play.

Performance Update: Q3 2023 was fantastic as planned; we were on track with our
targets.




BUSINESS MODEL


Our business model as a B2B SaaS provider is based on subscription fees that are
customized to meet the specific needs of our clients.

> The subscription fee ranges from $ 1,000 to $3600 per year, per building or
> location, based on the suite of products and use cases covered. Our contracts
> are typically one year in length, but we do have a few multi-year contracts.
> The average size of our contracts (ACV) with our clients is $31,000 annually.

In the future, given the size and volume of the data we collect, we can have
additional revenue streams from better AI-based predictive modeling and charging
a percentage of ROI generated for our clients.




MARKET & CUSTOMERS


Now is the best time to be in this business.

The multifamily sector is more inclined toward making data-driven decisions than
ever and is increasingly improving innovation budgets toward this issue.
(Source)

Since the idea's inception, the team has pursued ongoing research to understand
the makeup of the overall market and design solutions that solve critical
problems the relevant customer segment faces.

There are over 47 million rental assets across North America with growing
institutional funding in the residential space due to the low performance of
other real estate asset classes during the pandemic; this number is estimated to
grow tremendously over the next few years. In the U.S. alone, the housing stock
is worth over $33 trillion. Globally, the commercial real estate market is on
track to reach $4.3 trillion by 2025.

ALT

Image source here.

> Looking top down, a report indicates that the Global Business Intelligence
> Market stood at USD 24.59 Billion in 2022, with projections estimating its
> growth to USD 41.94 Billion by 2030. This represents a Compound Annual Growth
> Rate (CAGR) of 6.90% over the forecasted period.

> Furthermore, the Artificial Intelligence (AI) sector within the Real Estate
> Market, which encompasses IoT, was valued at USD 163.46 Billion in 2022. This
> figure is anticipated to surge to USD 1335.89 Billion by 2029, growing at a
> remarkable CAGR of 35%. (Source)

> If we take into account that North America represents approximately 50% of the
> global market in both the BI and AI domains:
> Assuming a modest 5% of the overall BI market is attributed to the real estate
> sector, the 2022 BI market size for real estate in North America is roughly
> USD 0.615 billion (50% of 5% of USD 24.59 billion).
> 
> On the AI front, considering a 20% allocation of our referenced AI market data
> to areas excluding IoT, the 2022 AI market size for real estate in North
> America amounts to USD 32.69 billion (20% of USD 163.46 billion), totaling $33
> billion.

> Projecting forward to 2030:
> The real estate BI market is expected to reach approximately USD 1.048 billion
> (50% of 5% of USD 41.94 billion).
> 
> The AI segment is forecasted to hit around $267.17 billion (20% of USD 1335.89
> billion), culminating in an aggregate of $268.22 billion.

To give more perspective to this top-down analysis, the specific estimated value
of the global property management software market will be over $14.89 billion in
2021. And now, given the improved awareness, pandemic-driven implementation is
expected to grow to over $32.61 billion in the next ten years at a CAGR of 8.7%
(Source). This shows that the AI market size in real estate is much bigger than
the property management software market, given the AI tools can be utilized by a
much larger user base beyond property management, including capital allocators,
asset managers, developers, etc.

> Our product serves users across the asset lifecycle in residential space from
> capital allocators, ownership groups, and asset & property managers; top
> groups constitute only 6% of the total segment of owners and operators but is
> responsible for over 54% of the rental assets and dominates the activity
> across North America. This segment is expected to continue its dominance over
> the coming years.

The investment volume for multifamily surpassed $213 billion in 2021. This is
more than double the $96 billion total recorded in 2020 and well above the
previous investment peak recorded in 2019 of $129 billion (Source).

The market is highly concentrated in this segment towards the selected few. Our
strategy involves targeting enterprise customers first to ensure the
establishment of market leadership, long-term growth, and volume with a
sustainable LTV/CAC ratio.

Here are some key insights that have led us to develop the product and focus on
this niche:

Over 80% of all enterprise rental management firms offer marketing, leasing,
rent collection, leasing, and repairs as part of their service offering.

An enterprise rental manager typically uses 4-5 different software across the
rental journey.

Most managers feel that the lack of available data is a major issue in
championing improvement and decision-making in the renting processes followed by
their companies.

Manual processes and expensive resources lead to a general overwhelming in the
rental management industry and usually understaffed teams. The average wage of a
property manager in North America is $35.20 per hour or $73,210 per year.

Growth and efficiency are the top-most priorities indicated by a pool of over
2000 property managers surveyed representing all 50 states.

Read a few articles by top VCs about the opportunity in this space: a16z, Alpaca
VC, Navitas Capital, and JLL.

You can review more data points and insights from our customer research here.

MUST SEE: Intrigued but not convinced? You should also check out our bottom-up
market sizing math here.




COMPETITIVE LANDSCAPE


Our competitive landscape consists of various software options, including niche
offerings that overlap with our product and modern multifamily property
management suites that feature some business intelligence elements.
Additionally, there are generic software options like Power BI, which requires
clients to invest tens of thousands of dollars in developing dashboards and
maintaining resources.

Despite this, we are confident that we will continue to succeed and introduce a
new era of data-driven decision-making to the industry.

Our competitive advantage stems from two main factors:

First, we have developed predictive and descriptive AI models and recommendation
engines that are trained on real estate specific data sets alongside
conversational AI components. These models enable us to predict, forecast, and
suggest actions in advance, leading to proactive bottom-line growth. This makes
it far more valuable than simply reviewing data and generating insights. Our
prescriptions become tailored to our client's decision-making strategies,
insinuating higher product utilization and stickiness over time.

Second, we are 10x faster to implement and start with any other solution
providers in this segment. Our solution does not require sophisticated data or
IT teams to implement, making it accessible to a wide range of organizations.

These two factors combined make Leni a highly effective solution that
outperforms most indirect competitors and enables asset managers to expand their
portfolios and improve their bottom lines without large team requirements.

See our comparative analysis of the landscape here.

This competitive advantage is evidenced by the fact that some of the most
prominent rental managers signed up for Leni within the first few months of our
launch, even though they were using some of the leading software in the space.

Current clients include:

ALT

Hear from our clients: Check out this Zoom interview with one of the users. They
use Leni for top-line decision-making and revenue management.




GO TO MARKET


Our primary focus is on large enterprise rental managers, particularly those
overseeing over 6,000 units. This specific segment, while only making up 12% of
landlords, is responsible for managing an impressive 72% of rental assets across
North America, translating to over 30,000 institutions.

We are actively engaging this market segment with a three-pronged go-to-market
strategy:

Outbound Strategy: We directly reach out to potential clients, showcasing our
product's capabilities and its direct relevance to their unique needs. Given the
geographical spread of multifamily assets, we offer clients the chance to pilot
our product with a specific portfolio or regional team. This strategy aligns
perfectly with our enterprise sales approach, where we secure a contract
(typically starting at $15,000 annually) and then broaden the implementation
based on the client's requirements and potential.

Distribution Partner Relationships: We are cultivating strategic relationships
with key distribution partners to extend our reach. These partners range from
businesses serving our target market to industry associations and real estate
platforms. By leveraging these partnerships, we are enhancing our market
visibility and credibility.

Content Marketing-Based Inbound Strategy: We consistently produce and
disseminate high-value content that resonates with our target audience. This
includes insightful blog posts, comprehensive white papers, engaging webinars,
and dynamic social media content that underscores the advantages of data-driven
decision-making in real estate investment. By establishing ourselves as industry
thought leaders, we attract potential clients to Leni.

This strategy has already yielded results, allowing us to land and expand with
enterprise clients. We have seen accounts grow to over $60,000 in annual value
within a year of implementing this strategy. Our revenue retention rate is 140%,
and we believe that continued efforts in establishing strong channel partners
alongside a more content-driven inbound strategy will help us scale GTM
effectively.

We have great initial traction with ten enterprise clients within the last ten
months of the public launch, with an average annual contract value (ACV) of
$31,000. We have 30+ similar clients in the pipeline, resulting in over $1MM in
pending contracts and expansion revenue.




FREQUENTLY ASKED QUESTIONS (FAQS)


1. We would like more understanding of your go-to-market. How did you get the
current enterprise clients (e.g., Oxford, CAPREIT, etc.)? How will you expand
beyond these users?

2. Does Leni have access to proprietary data from these real estate companies?

3. Has Leni made any special arrangements to access data?

4. What are the alternatives to direct enterprise sales in your go-to-market
strategy?

5. What does the sales cycle look like?

6. Can a shared customer exist (e.g., can customers work with Leni and Knock
CRM)? Is there any advantage to using just your platform, or are your customers
using multiple platforms from your vertical?

7. How hard is it to switch vendors? For example, is anything stopping a
customer from jumping ship to another platform?

8. How can the ecosystem benefit from Leni, and what's your strategy to recruit
them?

9. How does the Total Addressable Market (TAM) for Leni present a compelling
investment opportunity, given its unique offerings and the current PropTech
landscape?

10. Given the nature of this industry, we needed help to get our heads around
the pathways to expand ACV amongst enterprise clients and the overall depth and
breadth of the rental management data market. Can you explain your strategy
here?

11. Please describe your decision process in prioritizing features for your
product, including where you get inspiration, how your internal team (sales &
engineering) and customers contribute to this process, and how you distinguish
must-have features vs. nice-to-have features.




CONTACT


In case you are interested in chatting about the opportunity. Give us a call, or
feel free to book a time in my calendar here.

ALT