CityScale is a housing data platform that aggregates disparate information—ranging from real estate prices and crime rates to pollution and transportation—into an interactive map. The deck positions the company as a solution for citizens, private companies, and government authorities to make informed decisions about living environments. Notably, the presentation emphasizes the platform's utility in humanitarian contexts, specifically for refugees and post-war rebuilding efforts. While the deck showcases a functional product and a third-place win at the 5th EU Datathon (earning 5000 EUR), it i…
Key takeaways
- The platform aggregates open data on prices, crime, pollution, transportation, and health facilities from both government and private sources (Slide 6).
- CityScale employs a freemium business model, offering refined data distribution via a portal and API, alongside valuation services (Slide 12).
- A significant portion of the value proposition is dedicated to post-war rebuilding and helping refugees find better shelter (Slide 11).
- The product is already live, featuring an interactive map with specific metrics like 'Conditions valuation' and 'Ecology' scored out of 10 (Slide 7).
- The company achieved 3rd place in the 5th EU Datathon, receiving a 5000 EUR prize (Slide 15).
- The deck lacks a team slide, providing no information on the founders' backgrounds or technical expertise.
- There are no financial metrics, user growth numbers, or a specific capital requirement listed anywhere in the 16 slides.
- The long-term vision is to scale the platform globally to any location where people live (Slide 13).
Slide-by-Slide Analysis
The Vision and Problem (Slides 1-5)
Slide 1: Title The deck opens with the company name, CityScale, and the tagline 'Where is better open data-driven housing.' It includes a URL pointing to a Ukrainian domain (.com.ua), establishing the company's geographic roots.
Slide 2: Our goal The stated goal is 'To change how we choose a place to live.' The slide argues that choosing a home takes too much effort and responsibility due to the complexity of modern living. This is a high-level emotional hook but lacks specific data on the 'effort' involved.
Slide 3: Existing solutions The deck critiques current market players. Live agents are described as 'limited capacity, biased, opinionated.' Ordinary real estate services are called 'cluttered' and accused of prioritizing property and sellers over the buyer's needs.
Slide 4: The problem This slide clarifies the niche: 'They won't tell you what is behind the walls.' It emphasizes that while an apartment can be fixed, the surrounding environment cannot. This sets the stage for a data product focused on neighborhood quality rather than just floor plans.
Slide 5: Reviews, maybe?... The founders dismiss user reviews as a primary solution, noting they are subjective, unstructured, incomplete, and potentially fake. This justifies the need for an objective, data-driven approach.
The Solution and Product (Slides 6-9)
Slide 6: What we do?... CityScale aggregates open data regarding real estate prices, crime, pollution, transportation, and educational/medical facilities. Crucially, they state they use both government and private data sources to create 'simple model valuations.'
Slide 7: Product Screenshot This is the most informative slide in the deck. It shows a functional map of Kyiv with color-coded data points. A pop-up box displays specific scores: 'Conditions valuation 6/10', 'Crimes 7/10', 'Ecology 6/10', and 'Transportation 4/10'. The interface includes filters for budget, rooms, floor, and points of interest. This proves the product is more than a concept.
Slide 8: Beyond visualization The company mentions experiments with 'smart agents' and chatbots. They also highlight the provision of raw data and APIs for professional use, suggesting a B2B layer to the business.
Slide 9: How it works for people?... This slide summarizes the user benefit: seeing the 'whole picture at a glance' to make 'conscious decisions with less effort.' It frames the outcome as 'fair housing and better living.'
Market and Sustainability (Slides 10-13)
Slide 10: Sustainability: target audiences The deck lists citizens, private companies, city specialists, and authorities as targets. The use of the word 'Sustainability' here refers to the longevity of the business model through diversification rather than environmental impact.
Slide 11: Sustainability: war and post-war This slide addresses the current geopolitical context of Ukraine. It positions CityScale as a tool for refugees and displaced persons seeking shelter and as a foundation for 'effective post-war rebuilding based on computer data analytics.' This is a powerful, mission-driven pivot.
Slide 12: Diversified services. Business model The model is 'Freemium.' Revenue comes from 'Refined open data distribution' via portal and API, and 'Life condition valuations as a service.' No pricing tiers or projected ARPU (Average Revenue Per User) are provided.
Slide 13: Sustainability: ultimate scaling The founders claim the platform is built to feed data for 'any location around the world where people live.' This asserts global ambitions but provides no roadmap for international data acquisition.
Current State and Contact (Slides 14-16)
Slide 14: Current state The company claims to be working with local and international partners and is 'shaping European market expansion.' No specific partners are named.
Slide 15: 5th EU Datathon Winner This slide provides external validation. CityScale took 3rd place in an EU-wide competition, winning 5000 EUR. This confirms the technical viability of their data processing.
Slide 16: Contacts The deck concludes with social media links and a feedback email. There is no 'Ask' slide detailing how much money they are raising or what the funds will be used for.
What Works
Clear Product Demonstration: Slide 7 is excellent. It shows exactly what the user sees, the metrics being tracked, and the level of granularity in the data. · Strong Problem Definition: The distinction between 'fixing an apartment' and 'fixing an environment' (Slide 4) is a compelling way to explain why neighborhood data is a separate, valuable asset class. · Social Impact Alignment: The inclusion of post-war rebuilding and refugee support (Slide 11) gives the project a sense of urgency and moral purpose that can appeal to impact investors and government grants. · External Validation: Citing the EU Datathon win (Slide 15) provides immediate credibility for a data-heavy startup.
What is Missing
The Team: There is no mention of who is building this. Investors need to know if the founders have the data science, urban planning, or real estate expertise to execute this vision. · The Ask: The deck ends without asking for anything. A fundraising deck must specify the amount being raised, the valuation (or cap), and the milestones the funding will achieve. · Financials and Metrics: There are no mentions of current user numbers, API pings, revenue, or growth rates. Even for an early-stage company, some indication of traction beyond a contest win is necessary. · Competition: The deck ignores existing competitors like Zillow (Neighborhood scores), Localize.city, or various open-data government portals. · Unit Economics: While a 'freemium' model is mentioned, there is no explanation of the cost of data acquisition versus the revenue generated per professional user.
Founder Recommendations
Add a Team Slide: This is the most glaring omission. Highlight the technical lead's experience with GIS (Geographic Information Systems) and open data. · Quantify the Market: Instead of saying 'any location around the world,' identify the specific European markets you are targeting next and the size of the real estate data market in those regions. · Define the 'Ask': If this is a pitch deck, you must tell the investor what you need. For example: 'Raising $500k to expand data coverage to 5 additional European cities and launch the B2B API.' · Show User Traction: If you are 'working with local and international users,' show a graph of monthly active users (MAU) or a list of logos for your B2B partners. · Clarify Data Sourcing: Open data is notoriously messy. A slide explaining your proprietary 'processing' (mentioned on Slide 6) would help demonstrate a technical moat.
Frequently asked questions
- What is the core problem CityScale aims to solve?
- According to Slide 2 and Slide 4, the problem is the 'scale, volume and complexity of living.' Existing solutions like real estate agents are described as biased or limited, while standard services prioritize sellers. CityScale focuses on what is 'behind the walls'—the environmental factors like crime and pollution that are harder to fix than a physical apartment.
- How does CityScale generate revenue?
- Slide 12 outlines a 'Freemium' business model. Revenue streams include refined open data distribution through a portal and API, as well as 'Life condition valuations as a service.' The deck describes the freemium approach as a 'social responsible model,' suggesting a mix of free public access and paid professional tools.
- Who is the target audience for this platform?
- Slide 10 identifies a diversified target audience including current and future citizens, private companies, city specialists, and government authorities. Slide 11 further specifies refugees and temporary displaced persons as a key demographic, particularly in the context of post-war rebuilding.
- What technical features are highlighted in the deck?
- Beyond data visualization on interactive maps (Slide 7), Slide 8 mentions experiments with 'smart agents' like chatbots to increase accessibility. The platform also provides raw data and APIs for professional users, indicating a developer-friendly infrastructure intended for scaling.
- What evidence of traction is provided?
- The primary evidence of traction is the product screenshot on Slide 7 and the award mentioned on Slide 15. The company won 3rd place at the 5th EU Datathon in the 'An economy that works for people' challenge, which included a 5000 EUR prize. Slide 14 also states they are 'working with local and international users.'
