The real-world social layer for modern cities.

People are digitally connected but socially disconnected. Existing platforms are either online-first, dating-first, professional-only, or content-driven. They do not solve the core problem of helping people discover and meet relevant people around them in real life. Crosspolitan turns shared physical context into trusted, intent-based introductions.

Crosspolitan is an AI-powered real-world social discovery platform built around proximity, venue check-ins, user intent, privacy-controlled visibility, and contextual matching. It helps users discover people nearby or connected to the same places, then move from digital discovery to real-life interaction.

Urban loneliness, remote work, digital fatigue, fragmented social apps, and the decline of spontaneous in-person interaction have created a clear market gap. At the same time, AI can now improve relevance, trust, ranking, and safety. The timing is right for a privacy-first, in-person-first social discovery layer.

Crosspolitan is not dating-first. Users select intent across friendship, networking, business, events, dating, or open context. The platform is built around shared places and real-world proximity, not endless swiping. Dating can exist inside the platform, but the larger category is social discovery.

The initial users are urban professionals, entrepreneurs, expats, travelers, students, remote workers, and socially active people in cosmopolitan cities. The target user already spends time in cafes, hotels, coworking spaces, restaurants, events, gyms, universities, and nightlife venues, but lacks a trusted layer to discover relevant people in those contexts.

Users currently rely on fragmented tools: Instagram, LinkedIn, WhatsApp groups, Meetup, Bumble, Tinder, Eventbrite, coworking communities, private groups, and offline social luck. None of these creates a unified real-world discovery layer based on proximity, check-ins, intent, and venue context.

Users adopt Crosspolitan because it reduces the friction of meeting relevant people in real life. The value is strongest when the user is already in a high-intent physical context: a venue, event, hotel, coworking space, university, conference, or city hub. The product becomes useful when it helps users know who is nearby, why they are relevant, and whether there is mutual intent to connect.

Some behavior change is required, but it is limited. Users already check locations, join events, browse profiles, and message people. Crosspolitan adds one new behavior: controlled visibility inside shared physical contexts. The product must make check-ins and intent selection fast, low-friction, and privacy-safe.

Crosspolitan sits at the intersection of social networking, dating, professional networking, local discovery, events, and venue activation. This expands the opportunity beyond dating. The commercial thesis is that a real-world social layer can monetize through paid memberships, in-app features, venue SaaS, sponsorships, events, and partner activations.

Direct and indirect substitutes include dating apps, social media platforms, professional networking tools, event platforms, meetup communities, venue communities, WhatsApp groups, and offline introductions. The key difference is that Crosspolitan is built around real-world co-presence, intent, and venue context, not just online profiles or content feeds.

The competitive advantage is the combination of proximity, check-ins, intent, trust signals, privacy controls, venue context, and post-interaction feedback. This creates a proprietary IRL signal graph that online-first platforms cannot easily replicate.

The moat is the proprietary IRL signal graph. Every check-in, co-presence event, intent signal, venue pattern, mutual interest, safety signal, and post-meet feedback loop improves future matching. The AI model alone is not the moat. The proprietary real-world interaction data is the moat.

A user checks in at a venue or enters a visibility window. The user selects intent. Crosspolitan ranks relevant nearby users or people connected to the same venue context. Users can express lightweight mutual interest. If there is alignment, the platform facilitates an introduction or real-world interaction. Privacy controls define who can see whom, when, and under what context.

Crosspolitan has a diversified revenue model: paid memberships, advanced radar and filters, visibility boosts, AI introductions, event access, Venue SaaS, sponsorships, local campaigns, and partner activations. The Venture Base Case does not depend only on subscriptions.

The Venture Base Case projects €58M in Year 5 revenue. The revenue mix is: €28M paid memberships, €9M in-app features and boosts, €7M Venue SaaS, €8M sponsorships and local campaigns, and €6M events and partner activations. Membership revenue is supported by 135K average paid members and approximately €17.30 monthly membership ARPPU.

User acquisition is city-based and blended. The model assumes paid acquisition, venue-led acquisition, ambassadors, referrals, local communities, founder and professional groups, universities, expat clusters, hotels, coworking spaces, and curated IRL events. CAC is not modeled as pure paid media CAC.

The Venture Base Case assumes blended CAC per registered user rising from €1.20 in Year 1 to €2.50 in Year 5. Growth acquisition spend increases from €240K in Year 1 to €5.50M in Year 5. Effective CAC per new paid member ranges from €78 to €96. These assumptions depend on venue-led acquisition, referrals, ambassadors, events, and city-density effects.

The key metrics are registered users, Average MAU, monthly real-world interaction users, average paid members, paid conversion of MAU, blended CAC, growth spend efficiency, venue partners, D30 retention, report rate, revenue, EBITDA, cash position, and city-level liquidity. The North Star Metric is monthly active users with at least one real-world interaction.

Round 2 is milestone-based, not automatic. The target gates are: working MVP with radar, check-ins, profiles, privacy controls, analytics, and AI matching v1; 10,000 registered beta users; 2,500 monthly real-world interaction users; 50 active venue partners; D30 retained active users above 10 percent; report rate below 2.5 percent; early paid conversion; venue willingness to pay; and an investor KPI dashboard live before scale spend.

Crosspolitan scales city by city. The company first proves density, retention, safety, venue activation, and paid conversion in one city. It then replicates the playbook across cosmopolitan hubs. The model assumes 1 to 2 active city markets in Year 1, 3 to 5 in Year 2, 7 to 10 in Year 3, 15 to 20 in Year 4, and 25 to 35 in Year 5.

The main bottlenecks are local liquidity, trust and safety, CAC inflation, retention, venue density, and operational execution. The company mitigates these through controlled beta cohorts, venue clusters, ambassador-led growth, privacy-first design, safety controls, and milestone-based capital deployment.

The Venture Base Case projects revenue of €650K in Year 1, €3.8M in Year 2, €11.5M in Year 3, €27.5M in Year 4, and €58M in Year 5. EBITDA is projected at negative €600K in Year 1, negative €200K in Year 2, positive €2.2M in Year 3, €8.9M in Year 4, and €22M in Year 5.

Crosspolitan reaches EBITDA breakeven in Year 3 under the Venture Base Case. This is EBITDA breakeven, not free cash flow breakeven. Taxes, capex, and working capital may affect actual cash generation.

Round 1 is €300K for 10 percent equity, implying a €3.0M post-money valuation. Round 2 is targeted at €850K for 8 percent equity, implying a €10.625M post-money valuation. Round 2 is targeted for Q1/Q2 2027 and is conditional on milestone achievement.

Round 1 funds MVP product and backend, founder and core team runway, pre-launch growth, beta cohort, legal setup, privacy architecture, venue activation, trust and safety foundations, reserve, and investor readiness. It is a proof budget, not a scale budget.

Crosspolitan is designed to be capital-efficient compared with traditional consumer app rollouts. It uses contractor-heavy product development, venue-led acquisition, ambassador-led growth, referral loops, and city-by-city expansion. The model assumes the company earns the right to scale only after city liquidity and retention are proven.

The main risks are local liquidity risk, privacy and safety risk, paid conversion risk, CAC inflation, execution risk, capital risk, and gross margin risk. These are mitigated through city-by-city rollout, venue clusters, privacy controls, reporting and blocking workflows, milestone-based capital, lean burn, contribution margin tracking, and delayed expansion if KPIs are not met.

The company succeeds if it proves that users consistently create real-world interactions and that those interactions drive retention, paid conversion, venue value, and city-level network effects. The company fails if it cannot create sufficient local liquidity, cannot control safety and privacy risk, or cannot keep blended CAC within target ranges.

Likely exit options include acquisition by a social platform, dating platform, professional network, local discovery company, event platform, travel or hospitality group, or consumer internet company seeking a real-world social graph. Later-stage secondary liquidity or IPO would be possible only if Crosspolitan reaches substantial scale.

Investor returns are paper returns until a liquidity event occurs. Liquidity could come through acquisition, secondary sale, later financing with partial liquidity, or IPO. The model shows potential value creation by Year 3 and Year 5, but actual liquidity is not guaranteed.

Round 1 investors enter at €3.0M post-money and are modeled to retain approximately 9.2 percent after Round 2. At a €50M Year 3 implied enterprise value, the Round 1 stake is worth approximately €4.60M, representing 15.3x MOIC. At a €220M Year 5 implied enterprise value, the Round 1 stake is worth approximately €20.24M, representing 67.5x MOIC. These are modeled scenarios, not commitments.

The team combines founder-led consumer brand building, international expansion, legal and IP experience, strategic partnerships, and senior software architecture. The immediate execution requirement is not to build a global company overnight. It is to build the MVP, prove one dense city, track the right KPIs, and earn the next round.

Crosspolitan offers early entry into a venture-scale consumer network with local marketplace economics. The company is not being financed as a small dating app. It is being financed as an AI-enabled real-world social layer with multiple monetization streams, a proprietary IRL signal graph, and a milestone-based capital plan. The risk is high, but the entry valuation creates meaningful asymmetric upside if city liquidity and monetization are proven.