How much did RealFriend raise with this deck?

According to the catalogue facts, RealFriend raised $4.4M in a Seed round in 2020. Interestingly, the deck itself does not include a slide specifying the amount being raised or the valuation sought, which is common in decks designed for initial interest rather than final closing.

What is the core business model of RealFriend?

As stated on slide 12, the business model is a referral-based system. RealFriend collects a 25% referral fee from real estate agents who work with the platform. They estimate the total addressable market for these fees at $10 billion, derived from a larger $100 billion pool of real estate commissions.

How does the company measure product success?

RealFriend relies heavily on Net Promoter Score (NPS) and engagement growth. Slide 11 shows an NPS of 65 in Tel Aviv and 40 in New York. They also cite a 'Product-Market Fit' metric on slide 9, stating that 60% of users would be 'very disappointed' if they could no longer use the service.

Who are the founders and what is their background?

The founders are Luke (based in NYC) and Dooron (based in Tel Aviv). Slide 2 highlights that they have worked together for 15 years, served in the Israel Defense Forces (IDF) special forces, and have launched multiple businesses together previously.

What market problem does RealFriend aim to solve?

Slide 13 defines the problem as the 'headache and frustrating task' of finding a home to rent or buy in 2020. Their solution is a free AI assistant that performs the search on behalf of the user, leveraging the fact that millennials prefer chat-based communication (slide 7).

RealFriend Pitch Deck (2020): 14-Slide Seed Deck

See all 14 slides of the RealFriend pitch deck — a 2020 Seed deck — with a slide-by-slide teardown of what the deck does well and where it falls short.

RealFriend’s 14-slide deck from February 2020 is a masterclass in prioritizing user sentiment and engagement metrics over traditional financial projections. The company, which raised $4.4M in Seed funding, positions its AI assistant, 'Luke,' not as a tool, but as a 'friend' for home seekers. By showcasing an NPS of 65 in Tel Aviv and 40 in New York, the founders demonstrated product-market fit in a notoriously difficult sector. The business model is a straightforward 25% referral fee from agents, targeting a $10 billion referral market. While the deck lacks a detailed roadmap, competitor matr…

Key takeaways

The founders emphasize a 15-year working relationship and shared background in the IDF special forces on slide 2.
RealFriend positions itself as a 'Hybrid AI RealEstate assistant' that operates via 24/7 chat on slide 5.
The company claims to be the market leader in the Tel Aviv rental market, having interacted with 53.8K users in a city with 50K annual rentals (slide 8).
Engagement in the New York beta grew at 25% month-over-month as of February 2020 (slide 9).
The deck highlights a Net Promoter Score (NPS) of 65 in Tel Aviv, comparing it to aspiration brands like Tesla and Airbnb (slide 11).
The business model relies on a 25% referral fee from agents, targeting a $100B commission pool (slide 12).
The 'Why Now' slide notes that 60 billion messages are exchanged daily and millennials make up 40% of US home buyers (slide 7).
The deck completely omits a financial 'Ask' slide, a detailed use of funds, or a competitive landscape analysis.

RealFriend: The Conversational AI Approach to PropTech

RealFriend’s February 2020 pitch deck is a focused narrative on user experience and market traction. At a time when many PropTech companies were building complex web portals, RealFriend bet on a 'Hybrid AI' chat interface. This teardown examines how they used high-engagement metrics and founder pedigree to secure a $4.4M Seed round.

Slides 1-2: The Team and the Bond

The deck opens with a simple title slide (Slide 1) introducing 'Luke' and 'Dooron,' the two founders based in NYC and Tel Aviv respectively. The subtitle, 'Your AI assistant for all things real estate,' immediately establishes the product category. Slide 2 is the primary team slide, and it is notably light on specific past company names or titles. Instead, it focuses on the strength of the partnership: 15 years of working together, service in the IDF special forces, and a history of launching multiple businesses. This is a classic 'bet on the jockey' move, signaling to investors that the team is battle-tested and cohesive.

Slides 3-6: Vision and Product Experience

Slide 3 expands the vision beyond real estate, suggesting that the AI assistant model could eventually apply to loans, jobs, and cars. This is a common tactic to show a massive Total Addressable Market (TAM) beyond the initial niche. Slide 4 introduces the emotional hook: 'A relationship with a friend, not a website.' It uses a screenshot of a group text where a user introduces the bot to their mother, framing the AI as a trusted entity rather than just a tool. Slide 5 and 6 provide a deep dive into the product interface. The screenshots show 'Luke' (the AI) handling complex queries, scheduling showings, and providing data-driven insights (e.g., 'it's 11.5% lower than the average 1 bed apt in the area'). The product is described as 'Hybrid AI,' implying there may be human-in-the-loop elements to ensure accuracy.

Slide 7: The 'Why Now'

RealFriend justifies its existence through four key points on Slide 7 . They highlight that chat is the preferred medium for millennials, citing 60 billion messages exchanged daily. Most importantly, they note that millennials make up 40% of US home buyers. This slide successfully connects a demographic shift with a specific communication preference, creating a sense of urgency for a chat-based real estate solution.

Slides 8-11: Traction and Sentiment Metrics

The meat of the deck lies in its traction slides. Slide 8 focuses on Tel Aviv, where the company launched in 2018. They claim to be the market leader in rentals, having spoken with 53.8K 'friends' in a city where only 50K apartments are rented annually. This implies near-total market penetration. Slide 9 covers the New York beta, launched in March 2019. Key metrics include 2,500 monthly active users and 25% month-over-month growth in engagement. Slide 10 uses qualitative data, showing screenshots of users sending 'LUV U' messages and cat GIFs to the bot, reinforcing the 'friend' branding. Slide 11 is perhaps the most important slide in the deck. It plots RealFriend's NPS (65 in Tel Aviv, 40 in New York) against competitors and aspirational brands. They place Zillow at an NPS of -8 and 'AI assistants' like Alexa in the 30-40 range, positioning RealFriend as a superior user experience.

Slides 12-13: Business Model and Problem Statement

Slide 12 outlines a simple, scalable revenue model: a 25% referral fee from agents. They visualize this against a $100 billion commission market, identifying a $10 billion slice for referral fees. This clarity is helpful for investors who might worry about how a 'free' assistant makes money. Curiously, the 'Problem & Opportunity' slide ( Slide 13 ) appears near the end of the deck rather than the beginning. It reiterates that home searching is a 'headache' and offers the solution of having someone do it for free.

What Works in the RealFriend Deck

Focus on NPS: By highlighting an NPS of 65, the founders proved that users don't just use the tool—they like it. In a crowded PropTech market, high sentiment is a strong differentiator. · Founder History: The '15 years together' and 'Special Forces' callouts on Slide 2 provide a level of de-risking regarding team dynamics that is rare in Seed rounds. · Demographic Alignment: Slide 7 does a great job of explaining why a chat interface is the correct 'form factor' for the modern home buyer. · Traction vs. Market Size: Slide 8 provides a very specific comparison (53.8K users vs. 50K rentals) that makes their market dominance in Tel Aviv feel tangible.

What is Missing from the RealFriend Deck

The Ask: There is no slide detailing how much money is being raised, the valuation, or the specific milestones the funding will achieve. · Competitive Landscape: While they mention Zillow on the NPS slide, there is no comprehensive matrix comparing RealFriend to other AI-driven search tools or traditional brokerages. · Unit Economics: While they mention the 25% referral fee, they do not disclose the Customer Acquisition Cost (CAC) or the Lifetime Value (LTV) of a user, which are critical for a Seed-stage referral business. · Technology Deep-Dive: For a company calling itself 'Hybrid AI,' there is very little information on the proprietary nature of their tech or how they handle data ingestion from real estate listings.

Founder Lessons

Lead with the 'Who': If you have a long, successful history with your co-founder, make that a central pillar of your pitch. Investors at the Seed stage are buying the team as much as the idea. · Use Qualitative Proof: Don't just show charts. Screenshots of users actually enjoying your product (like the 'LUV U' texts on Slide 10) can humanize your data and make a lasting impression. · Benchmark Your NPS: If your Net Promoter Score is high, don't just state the number. Compare it to the industry standard and the 'gold standard' brands to give it context, as seen on Slide 11. · Keep the Business Model Simple: RealFriend didn't overcomplicate their revenue. A single, clear percentage (25% referral fee) is much easier to sell than a multi-tiered subscription model in an early-stage deck.

Frequently asked questions

How much did RealFriend raise with this deck?: According to the catalogue facts, RealFriend raised $4.4M in a Seed round in 2020. Interestingly, the deck itself does not include a slide specifying the amount being raised or the valuation sought, which is common in decks designed for initial interest rather than final closing.
What is the core business model of RealFriend?: As stated on slide 12, the business model is a referral-based system. RealFriend collects a 25% referral fee from real estate agents who work with the platform. They estimate the total addressable market for these fees at $10 billion, derived from a larger $100 billion pool of real estate commissions.
How does the company measure product success?: RealFriend relies heavily on Net Promoter Score (NPS) and engagement growth. Slide 11 shows an NPS of 65 in Tel Aviv and 40 in New York. They also cite a 'Product-Market Fit' metric on slide 9, stating that 60% of users would be 'very disappointed' if they could no longer use the service.
Who are the founders and what is their background?: The founders are Luke (based in NYC) and Dooron (based in Tel Aviv). Slide 2 highlights that they have worked together for 15 years, served in the Israel Defense Forces (IDF) special forces, and have launched multiple businesses together previously.
What market problem does RealFriend aim to solve?: Slide 13 defines the problem as the 'headache and frustrating task' of finding a home to rent or buy in 2020. Their solution is a free AI assistant that performs the search on behalf of the user, leveraging the fact that millennials prefer chat-based communication (slide 7).

Cover slide of the RealFriend pitch deck — Seed 2020 — RealFriend pitch deck, slide 1 (2020)

RealFriend pitch deck: the facts

Company: RealFriend
Year: 2020
Stage: Seed
Slides: 14
Sector: PropTech
Deck type: Seed Pitch Deck
Outcome: Raised $4.4M
Headquarters: New York / Tel Aviv

RealFriend pitch deck PDF

The full RealFriend deck is embedded on this page and can be read slide by slide in the browser — no download or account required. Each slide is covered in the breakdown above.

What the RealFriend pitch deck was used for

RealFriend is a PropTech startup that developed Luke, an AI‑powered real estate chatbot that helps people find and buy apartments and homes through conversational search. The deck in question is a 14‑slide Seed‑stage presentation from 2020, used while the company was expanding Luke from its initial beta in Tel Aviv to an official launch in New York. The deck positions Luke not just as a tool but as a trusted ‘friend’ who provides curated listings, deep market insight, and 24/7 guidance, and it highlights engagement growth and high NPS in its primary market (per the existing article excerpt). It also presents a referral‑fee business model where RealFriend takes a percentage of brokers’ commissions, aiming at a large commission‑fee addressable market.

Business model: AI chatbot that helps renters and buyers search for and buy apartments and homes via conversational text, earning referral fees from real estate brokers on successful transactions.

Round: Seed
Year: 2020
Founded: 2018
Founders: Hadar Landau, Omri Klinger
Headquarters: 18 West 18th Street, New York, NY 10011, United States.
Industry: PropTech / Real Estate / Conversational AI.

Raised: Approximately $4–4.4M in Seed funding, as reported by third‑party fundraising and pitch‑deck analysis sites that profile RealFriend’s 2020 Seed round.

Total funding: Approximately $4–4.4M in Seed funding, as reported by third‑party fundraising/pitch‑deck analysis sources.

Use of funds as presented: Public analyses indicate the Seed capital was used to scale Luke’s AI assistant from its initial Tel Aviv deployment to broader operations in New York, refine the product, and pursue the referral‑fee business model in the real‑estate market.

What happened after the RealFriend deck

Following its 2020 Seed‑stage fundraising period, RealFriend’s Luke chatbot transitioned from beta in Tel Aviv to active deployment in New York, accumulating tens of thousands of user interactions and facilitating numerous leases and at least one highlighted home purchase, while continuing to operate as a conversational AI assistant for real‑estate transactions.

Luke evolved from Dooron in Tel Aviv to a New York–focused chatbot, going live in New York around mid‑2020 and later exp
By late 2020, Luke had reportedly interacted with around 40,000 individuals and helped secure about 1,000 signed leases,
Luke facilitated at least one notable home purchase, a $1.15M apartment in Carroll Gardens, Brooklyn, highlighted in New
RealFriend continued to develop Luke and related offerings (e.g., TextLuke) and maintained its positioning as an AI real

What the RealFriend deck got right

Compelling demonstration of user love and emotional engagement. The deck leverages highly emotive user testimonials (such as messages thanking Luke for help finding a future home and calling him their ‘only best friend’) to convincingly demonstrate deep user affinity and trust in the product experience.
Distinctive conversational AI product tailored to real estate. RealFriend’s product positioning as a hybrid AI personal assistant that uses conversational chat to search listings, provide insights, and guide users through closing offers a clear and differentiated user experience compared with traditional listing‑search websites.
Early traction metrics indicating strong engagement and satisfaction. The deck (and accompanying analysis) highlights concrete traction and satisfaction metrics, such as 25% month‑over‑month engagement growth and an NPS of 65, which provide investors with early evidence of strong product–market fit in the initial markets.
Clear referral‑fee monetization aligned with broker commissions. RealFriend articulates a straightforward revenue model—charging brokers a referral fee (around 25% of their commission) while keeping the service free to users—that aligns monetization with successful transactions and leverages existing commission structures.
Demonstrated operational traction and transaction impact. Press coverage cites thousands of users and a large number of leases facilitated (around 40,000 interactions and 1,000 leases by late 2020), which reinforces the deck’s claims about engagement and Luke’s ability to operate at scale in New York’s competitive real‑estate market.
Evidence of geographic rollout from Tel Aviv to New York. The narrative of expanding from Tel Aviv beta to New York launch, with Luke rebranded from Dooron, signals that the team can deploy and adapt the product across different geographies and regulatory contexts, which is attractive for investors seeking scalable PropTech platforms.

What could have been stronger

Heavy focus on qualitative user sentiment without clear financial linkage. The deck heavily emphasizes qualitative user love (e.g., the slide of chat transcripts saying users ‘love’ Luke and call him their ‘only best friend’) but does not, based on the available excerpt, connect that emotional engagement to hard metrics like conversion rates, unit economics, or revenue, making it harder for investors to tie user sentiment to financial outcomes.
Limited visibility into full conversion funnel within highlighted slides. External coverage cites operational traction (e.g., 40,000 interactions and 1,000 signed leases by late 2020) but the deck excerpt provided only mentions month‑over‑month engagement growth and NPS; investors reviewing this deck may find limited quantified funnel data (leads, leases, home purchases) directly presented on the user‑love slide.
Insufficient explicit treatment of structural and regulatory risks. While analyses note a referral‑fee model and a large commission‑fee TAM, the slide snippet about user love does not address regulatory, brokerage‑relationship, or customer‑acquisition risks, which may leave sophisticated investors with unanswered questions about defensibility and scalability.
Competitive and technical differentiation not strongly articulated on emotional slides. The deck’s positioning of Luke primarily as a ‘friend’ and emotional companion may under‑emphasize its differentiated data/AI capabilities (aggregation of listings, fraud filtering, advanced insights) that appear in press coverage, potentially making the competitive moat less explicit within the emotional‑storytelling slides.

How an investor would read this deck

What draws attention

Verification of the reported 25% month‑over‑month growth in engagement and NPS of 65 in the primary market against actual user and usage data from Tel Aviv and New York.
Detailed analysis of Luke’s traction metrics (e.g., number of conversations, leases signed, home purchases facilitated) as mentioned in press coverage, and how these map to the deck’s growth claims.
Assessment of the referral‑fee business model—especially sustainability of brokers paying a 25% cut of their commission to RealFriend and how that compares with industry norms in NYC and other markets.
Evaluation of RealFriend’s AI and data advantage: how Luke aggregates listings, filters out fraudulent content, and provides insights better than incumbent search portals.

Risks that stand out

Reliance on brokers’ willingness to share a significant portion of their commission (around 25%) could limit adoption or lead to margin pressure if competitors offer lower referral fees.
Increasing competition from large real‑estate portals and AI platforms that can build comparable chatbots and recommendation engines may erode Luke’s differentiation over time.
Regulatory or licensing constraints in different real‑estate markets may complicate scaling a bot that effectively behaves like an ‘agent’ without being a traditional licensed broker in every jurisdiction.
If engagement metrics and NPS do not translate into repeat usage and closed deals, the business could face a gap between strong user sentiment and sustainable revenue growth.
The product’s early concentration in New York and prior beta in Tel Aviv exposes RealFriend to localized housing‑market cycles and regulatory changes that could impact transaction volume.

Questions this deck invites

What verifiable metrics underlie the deck’s claim of 25% month‑over‑month growth in engagement and an NPS of 65 (e.g., cohort size, time period, markets)?
How many transactions (leases and purchases) did Luke directly influence in the 12 months surrounding the Seed raise, and what gross commission volume and referral‑fee revenue did that represent?
What is the detailed breakdown of the referral‑fee model (percentage, typical commission structures, contractual arrangements with brokers) and how has broker churn or resistance affected growth?
What proprietary technology, data integrations, or models power Luke’s conversational interface and listing insights, and how defensible are these versus larger real‑estate platforms building similar AI tools?
How has RealFriend’s expansion beyond New York (if any) impacted unit economics, regulatory exposure, and competitive dynamics in other markets?

What founders can take from the RealFriend deck

Anchoring the product narrative in a personable AI character (Luke) and showcasing real chat excerpts where users express love and gratitude can make a PropTech pitch feel human and emotionally engaging, which may help investors connect with the user experience.
Including explicit engagement and satisfaction metrics (25% month‑over‑month growth and NPS 65) alongside qualitative testimonials is a powerful way to demonstrate both emotional and quantitative traction in a Seed‑stage deck.
Framing a chatbot not merely as a tool but as a ‘friend’ that accompanies users through the stressful process of apartment hunting and home buying can differentiate an AI assistant in a crowded market.
A clear referral‑fee business model tied to existing broker commission structures helps investors quickly understand how an otherwise free consumer product will generate revenue and what the monetization lever is.
Showing that the product successfully launched in one market (Tel Aviv) and is rolling out to another (New York) demonstrates early proof of geographic scalability and real‑world adoption to investors.
Combining media coverage and quantified usage data (e.g., thousands of users and hundreds or thousands of leases) with the deck’s internal metrics can strengthen credibility if these numbers are aligned and well‑substantiated.

RealFriend pitch deck: common questions

What does RealFriend do?

RealFriend is a PropTech startup that built Luke, an AI‑powered chatbot and personal assistant that helps renters and homebuyers find apartments and navigate the real estate process through conversational text rather than traditional listing search.

Where and when was RealFriend founded?

Luke began as Dooron in Tel Aviv and was later launched in New York; RealFriend was founded in 2018 and is headquartered at 18 West 18th Street, New York, NY 10011.

How much did RealFriend raise with its 2020 Seed pitch deck?

The 2020 Seed pitch deck shows RealFriend raising a Seed round to scale Luke’s AI real estate assistant, with external sources indicating roughly $4–4.4M of Seed funding associated with this period, though precise round details and investors are not fully disclosed publicly.

How does RealFriend make money?

RealFriend’s business model, as described in public materials and pitch‑deck analyses, is to keep Luke free for users while charging real estate brokers a referral fee—around 25% of the broker’s commission—on deals that Luke helps close.

What problem does Luke solve for renters and homebuyers?

Luke offers conversational apartment and home search, sends curated listings, provides detailed insights on each property, and can answer nuanced questions about features, neighborhoods, and market conditions, functioning as a 24/7 hybrid AI assistant backed by real estate expertise.

Sources

Funding and outcome facts on this page were researched on 2026-08-22 from the pages below.

RealFriend pitch deck slides

RealFriend pitch deck slide 1 of 14 — RealFriend pitch deck — slide 1 of 14

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RealFriend pitch deck slide 3 of 14 — RealFriend pitch deck — slide 3 of 14

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RealFriend pitch deck slide 5 of 14 — RealFriend pitch deck — slide 5 of 14

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What each slide of the RealFriend pitch deck says

Slide 1

February 2020 Realfriend Your Al assistant for all things real estate - Luke - NYC Dooron - Tel Aviv

Slide 2

Who we are ? Founders working together for 15 Years, serving in special forces (IDF), Launched multiple businesses together Realfriend

Slide 3

Everyone, no matter who you are, deserves access to advice and mentorship when making life's biggest financial decisions Real Estate Loans Jobs Cars And more.. Realfriend

Slide 4

A relationship with a friend, not a website fe am Trusting an Al is one ° thing, INTRODUCING 2 HIM TO YOUR MOM rE © 0 Crown Height, Park Soe, 52.400 10 $3400, Pictures IS RESPECT mee re wo —— son if mm

Slide 5

Your Hybrid Al RealEstate assistant Available for you 24/7 in chat and answers like a friend © Hey, I'm Luke, your Al broker. Woop! Lod Let's find you the perfect place

Slide 6

apartment wih plenty of ight Hey, 50 how was the apt you just ground floor and a garden saw? Thoughts? ° Excellent! I'm on it. Wol, its 1.6% lower than the {found a great property, let verage 1 bed apt n the area. Its @ miirosenk pcb @ ‘memeuER le o Got Fm sorry that wasnt very nf TF a ‘good. 1% take note. Btw, if you are | ® oP p stil is the area? | have a great apt LL AR Te See 4 in wak from yous current it 5] Ane Tide location. It faces south with more ax] od (ENE ig an 2 spacious ing room. | ry Great ! happy to hear you love this ‘can arrange a viewing now while ally | ane Can shackle showing © roma " 4 @ tomorrows SP? 43 a Pr ———— pL 180d, 1 Bath, with full height windows | located on…

Slide 10

But they don't just chat with Luke, They love him! Wow! Thank you so much, Lukel!! These are great! Hi, Luke! Thank you for all your help in trying to find me my future home! My friends roommate moved out so I'm moving in with her. Thank you. With your help know I'll find a great spot. You're can't believe how helpful you have been thus far. LOL call me, beep me, if you wanna reach me. Thanks Luke You're like my only best friend.

Slide text above is read directly from the RealFriend deck PDF embedded on this page.