A psychographic-first AI matchmaking platform. Deep user understanding, multi-modal calibration, and adaptive matching — no swiping, no noise.
AIMM (AI Matchmaker) is a fully autonomous, AI-driven matchmaking platform that replaces swipe-based dating with calibrated, high-confidence match delivery. The system builds a deep psychographic model of each user through LLM-driven conversation, constructs a structured ideal partner profile, and resolves the contradiction between stated preferences and real attraction patterns through multi-modal calibration.
Unlike every existing platform — which either relies on user-curated swipe behaviour or shallow questionnaires — AIMM operates on three compounding vectors: psychological model, attraction vector, and behavioral adaptation. The result is a matching engine that improves with every interaction and surfaces fewer, better matches.
AIMM operates a two-phase revenue strategy: Phase 1 captures individual consumer subscription revenue through three paid tiers — targeting the premium and ultra-premium dating market, directly competing with elite matchmaking agencies charging $30K–$150K/year at a fraction of the cost. Phase 2 unlocks B2B licensing of the matching engine API to third-party apps, relationship platforms, and enterprise HR tools.
No free tier. Every onboard triggers LLM inference, image generation, and verification checks. Acquisition runs via 7-day money-back guarantee and referral discounts. Three tiers target progressively higher-intent users, with Concierge directly competing against elite matchmaking agencies at 1/5th the cost.
| Tier | Price / month | Features | Target |
|---|---|---|---|
| Premium | $49 | Psychographic profiling, multi-modal calibration, unlimited matches, stated income range preference, distance/radius filter, contradiction detection, behavioral adaptation | Core volume tier, ~55% of subscribers |
| Elite | $149 | All Premium + Plaid income verification badge (tier shown, balance never), GPS/address confirmation, national pool access, priority match queue, background check (basic), human matchmaker quarterly review | Verified professionals, 30–45 demographic, ~35% of subscribers |
| Concierge | $499 | All Elite + Government ID / passport scan (Stripe Identity), certified profile badge, HNW-exclusive pool, international matching, dedicated matchmaker, white-glove onboarding call, annual re-verification | HNW users, 35+ / post-divorce re-entrants. Competes with $30K–$45K/year agencies at $5,988/year. ~10% of subscribers, ~35% of revenue. |
| Metric | Value | Notes |
|---|---|---|
| Blended ARPU | ~$85/mo | Premium $49 (55%) + Elite $149 (35%) + Concierge $499 (10%) |
| Estimated CAC | $45 | Higher-intent audience, content + editorial + referral-heavy |
| LTV (12-month) | $680 | 8-month avg. retention at $85/mo blended |
| LTV:CAC | 15:1 | Significantly higher than previous model — fewer users, higher value |
| Concierge onboard COGS | ~$15 | Plaid + Stripe Identity + Checkr per user, one-time |
| Gross Margin | ~78% | Higher margin than before — verification COGS are one-time, not recurring |
| Monthly churn target | 6% | Lower churn expected — higher price = higher commitment, better matches |
AIMM's GTM is built on the insight that the early adopter is not the casual dater — it is the relationship-serious, quality-over-quantity user who has churned from swipe apps and is willing to pay for a fundamentally different experience.
500 curated users. Psychographic model calibration. No matching yet — pure profiling and interview refinement. Partner with 3 relationship therapists as advisors.
5,000 paying users. Live matching enabled. 7-day money-back guarantee on signup. Referral programme ($20 off first month for referrer and referee). Content strategy: "What your swipe history says about you."
Premium and Elite tiers go live. Press push: TechCrunch, Vogue, GQ (dual angle: tech + lifestyle). First cohort success stories published. Podcast sponsorships (relationship/psychology).
First B2B API partnerships. Expand to Toronto, Sydney, Berlin. 40,000+ users. Series A preparation. Begin white-label pilots.
Asia-Pacific entry (Singapore, Tokyo). Long-term relationship & couples product. Enterprise HR licensing. Multi-language psychographic model.
| Channel | Est. % of Users Y1 | Rationale |
|---|---|---|
| Organic / SEO | 35% | High-intent search ("why do I keep dating the wrong person") |
| Referral programme | 28% | Strong incentive — matching quality improves with mutual invites |
| Press & editorial | 18% | Dual angle: AI/tech + psychology/lifestyle |
| Influencer / podcast | 12% | Relationship psychology podcasts (niche, high-intent audience) |
| Paid social | 7% | Minimal Y1, scaled in Y2 once CAC is validated |
| Metric | Year 1 (2026) | Year 2 (2027) | Year 3 (2028) |
|---|---|---|---|
| Paying subscribers | 800 | 4,200 | 14,500 |
| — Premium ($49) | 440 (55%) | 2,310 (55%) | 7,975 (55%) |
| — Elite ($149) | 280 (35%) | 1,470 (35%) | 5,075 (35%) |
| — Concierge ($499) | 80 (10%) | 420 (10%) | 1,450 (10%) |
| Blended ARPU | ~$85/mo | ~$90/mo | ~$95/mo |
| Consumer ARR | $816K | $4.54M | $16.53M |
| B2B API ARR | — | — | $2M |
| Total ARR | $816K | $4.54M | $18.53M |
| Region | Year 4 ARR | Year 5 ARR | Year 6 ARR |
|---|---|---|---|
| 🇺🇸 North America | $22M | $30M | $40M |
| 🇬🇧 UK & Europe | $6M | $14M | $24M |
| 🇸🇬 Asia-Pacific | $1M | $5M | $13M |
| 🌐 B2B / API Global | $3M | $8M | $18M |
| Total ARR | $32M | $57M | $95M |
| Category | Monthly | Annual | % of Spend |
|---|---|---|---|
| Engineering (3 engineers) | $45K | $540K | 36% |
| LLM inference + infra | $12K | $144K | 10% |
| Marketing & content | $18K | $216K | 14% |
| Product / design | $15K | $180K | 12% |
| Operations & legal | $10K | $120K | 8% |
| G&A / misc | $8K | $96K | 6% |
| Total | $108K | $1.296M | 100% |
| Category | Amount | Purpose |
|---|---|---|
| Engineering & product | $1.35M | Build & scale core matching engine, mobile apps, infra |
| Marketing & growth | $750K | Waitlist launch, press, influencer, referral programme |
| AI/ML research | $450K | Psychographic model accuracy, vector database, bias auditing |
| Operations & legal | $270K | GDPR compliance, entity setup, advisor network |
| Runway reserve | $180K | 6-month buffer to Series A bridge |
| Risk | Category | Assessment | Mitigation |
|---|---|---|---|
| Cold start — sparse match pool | Product | High | Invite-only beta by geography. Matchmaking quality gated behind minimum pool size per city. Human matchmaker backstop during ramp. |
| LLM inference cost at scale | Technical | Medium | Profile built once, cached. Matching runs on vectors, not live LLM calls. LLM only re-invoked on calibration updates. |
| Regulatory — image analysis & biometrics | Legal | Medium | All image analysis is opt-in and consent-gated. No biometric storage — feature vectors only. External GDPR counsel retained from day one. |
| Attraction vector bias / homogeneity | Ethical | Medium | Diversity constraints baked into vector search. Quarterly bias audits. Explicit "broaden my pool" user control. Independent ethics board (advisory). |
| User trust — sharing psychological data | Market | Medium | Radical transparency UX — users see exactly what the model knows. One-click data deletion. No third-party data sales, ever. Privacy-first brand positioning. |
| Competition from Hinge / Bumble AI features | Competitive | Low | Incumbents are adding AI to swipe products — AIMM replaces the swipe product entirely. Structural difference, not a feature race. |
| Milestone | Target | Success Metric |
|---|---|---|
| Seed close | M+0 | $3M committed, lead investor signed |
| Beta launch (500 users) | M+3 | Psychographic model NPS ≥ 70 |
| First calibrated match delivered | M+5 | Match acceptance rate ≥ 60% |
| Waitlist public launch | M+6 | 5,000 registered users, 500 paying |
| Premium tier live | M+12 | $840K ARR run-rate |
| First press feature | M+9 | TechCrunch or equivalent Tier 1 coverage |
| Series A preparation | M+18 | $3M+ ARR, LTV:CAC ≥ 5x proven |
| B2B API first contract | M+20 | 1 signed partner, $10K+ MRR |
| International launch | M+24 | 3 cities outside US/UK, 5,000 intl users |
AIMM's competitive moat deepens with scale. The psychographic model improves as more users complete calibration. The behavioral layer gets sharper with more interaction signal. Each new user makes the system better for every other user — a data flywheel that incumbents cannot replicate by adding AI features to existing swipe products.
| Role | Requirement | Background |
|---|---|---|
| CEO / Co-founder | Product vision, fundraising, GTM | Consumer product background, prior startup exit or PM at Tier 1 |
| CTO / Co-founder | AI/ML architecture, vector systems | LLM fine-tuning, embeddings, PostgreSQL + pgvector experience |
| Head of Psychology / Advisor | Psychographic model validity | Relationship psychology PhD, attachment theory research |
| Lead Engineer | Backend infrastructure, API | Node/Python, real-time systems, GDPR-compliant data handling |
| Head of Design | UX, visual identity | Consumer apps, trust-sensitive product design |