Flexible pricing or revenue-sharing options. Contact us

Your benefits:

• Full platform customization. Want a dating site or app like your favorite ? Use our 200+ ready custom features, which include the same ones you love in your favorite app, to get started quickly, without a huge budget. Assistance with development, setup, and publishing to app stores
• Maximize your ROI with our flexible revenue-sharing model. Gain access to our complete toolkit and expert support to scale your business
• Get the Dating Pro platform with a ready-to-use website and apps already published on the App Store, Google Play, Huawei, and Samsung stores

Full list of features

Be one of the first to create powerful matchmaking success cases!

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We will enable it after we have a base of matches. AI matchmaking requires a sample for training:

The number of matches needed to train AI models on a dating platform depends on the model’s goals, level of personalization and algorithm complexity. Let’s look at a few scenarios:

a. Basic Recommendations (simple heuristics)

• Required Database: 1,000 to 10,000 matches
• Used for basic matching based on common criteria (age, location, interests).
• Suitable for MVP testing.

b. Machine Learning Model Training (logistic regression, Random Forest, LightGBM, etc.)

• Required Database: 50,000 to 500,000 matches
• Used to improve ranking, predict the likelihood of mutual interest.
• The more data, the better the algorithm identifies patterns.

c. Deep Neural Networks (DL, RNN, Transformer-based models)

• Required Database: 1,000,000 to 10,000,000+ matches
• Used for complex predictions, personalization of recommendations at the level of behavioral patterns (e.g., Tinder, Bumble).
• Requires a large amount of data for training without overfitting.

d. Recommender Systems with Reinforcement Learning (e.g., multi-armed bandit, deep Q-learning)

• Required Database: 10,000,000+ matches
• Optimized through continuous data collection and A/B testing.
• Used in large dating platforms like Tinder, where AI adapts to user behavior in real-time.

Conclusion:

• For testing recommendations mechanics - 100K matches can already give good results.
• To create AI that really understands users and makes cool recommendations - millions of matches.

We can integrate with almost all of the listed apps.

Some popular dating apps offer matchmaker cabinets or features that allow third parties (agencies, professional matchmakers, friends) to help in the search for a partner. Here are the main platforms that offer such features:

Matchmaker Cabinet Apps and Platforms

i. Tawkify

• Fully operates through professional matchmakers, without traditional swiping.
• Clients fill out questionnaires, and matching experts select candidates.
• No self-search, only curated matches.

ii. Three Day Rule

• VIP dating service where matches are selected manually by professional matchmakers.
• Works by subscription, with personal consultations.

iii. Lunch Actually

• Asian dating service based on real dates, not online chats.
• Matchmakers help find ideal couples based on personal preferences.

iv. LUMA (Luxury Matchmaking)

• Premium dating service for wealthy people.
• Entirely based on the services of matchmakers who guide clients personally.

v. VIDA Select

• Combination of AI and professional matchmakers.
• Matchmakers write messages, manage client profiles, and help at all stages.

Apps with Features for Matchmakers

i. Bumble BFF & Bumble For Friends* Not a traditional matchmaker, but a feature where friends can help find matches.

ii. Wingman

• Friends and relatives can select matches for their acquaintances.
• Not a classic matchmaker, but similar concept.

iii. SetMeUp

• An app where friends play matchmaker and help set up acquaintances.

iv. Paktor

• Popular in Asia, offers professional matchmaker services.

v. Seeking.com (formerly Seeking Arrangement)

• Although the main audience is specific, there are agents who find couples for a fee.

What About Tinder, Bumble, Hinge, OkCupid?

These apps are self-service focused and don’t have built-in matchmaker features. But professionals can use:

• Tinder Select / Hinge Preferred - VIP versions with priority matching.
• Bumble Premium - you can filter by more precise criteria.

Conclusion

If you’re looking to add matchmaker cabinets to a dating platform, this is a valid concept. It’s in demand in the premium segment, but niche in the mass market.

Roadmap

1. MVP (3 months)

• Gathering product requirements based on your expectations (matchmaking agency). Consideration of revenue share participation (works on a revshare model with Dating Pro https://help.datingpro.com/en/articles/6075512-partner-with-dating-pro-revenue-sharing-and-full-product-team-support )

Key Performance Indicators

Agency Metrics

• Lead to paying client conversion: 15-20%
• Average time to a successful match: 6-8 months
• Retention rate of paying clients: 85%
• Average check per client: $2,000-5,000
• Agency NPS: 80+
• Automation of routine processes: up to 70%

Client Metrics

• Successful matches: 65% within a year
• Conversion from first date to relationship: 30%
• Satisfaction with the selection of couples: 85%
• Willingness to recommend the agency: 75%

Technical Metrics

• Platform uptime: 99.9%
• Page load speed: <3 sec* Integration with dating sites: 70+%
• AI matching accuracy: 75%
• Attracting seed investments.

Investor Benefits

• The matchmaking market is growing by 4% annually
• Ready-made Dating Pro technology base with SLA support
• Quick market entry (3-6 months)
• Scalability to other countries
• Calculation of the financial model. For example:

Detailed Financial Model

Investments and Expenses

• MVP Development: $200,000
• Marketing and Promotion: $150,000
• Operating Expenses: $100,000
• Reserve: $50,000

Revenue Forecast (first year)

• Agency Subscriptions: $300,000
• Commission from additional services: $150,000
• Affiliate Programs: $50,000

Target Indicators (3 years)

• Revenue: $3M+
• EBITDA margin: 30%
• CAC/LTV: 1:5
• Retention rate: 80%
• Determine the basic functionality with CRM
• Integration with 2-3 popular dating sites
• Testing with first clients

2. Release (6 months)

• Full functionality for agencies
• Mobile app for clients
• Integration of paid services

Technical Implementation

Integrations

• With dating platforms
• Payment systems
• CRM and analytics
• Video conferencing and messenger integrations

Security

• End-to-end encryption
• Two-factor authentication
• GDPR compliance
• Regular audits

AI and Machine Learning

• Automatic pair selection
• User behavior analysis
• Predictive analytics
• Conversion optimization
• Marketing launch in channels

3. Scaling (12+ months)

• Entering international markets

Regional Specifics

Asia-Pacific Region

• Focus on traditional values
• Importance of family approval
• High demand for intercultural dating
• Need for localization to local languages
• Integration with WeChat and Line

Europe

• Strict GDPR requirements
• Multilingualism is mandatory
• High demand for premium services
• Importance of local expertise
• Integration with local dating servicesNorth America
• Focus on professional career
• High requirements for verification
• Importance of legal support
• Demand for VIP services
• Integration with LinkedIn
• AI for automatic matching
• Development of an ecosystem of additional services

Marketing Strategy

Agency Acquisition Channels

• Professional exhibitions
• B2B marketing
• Industry publications
• Affiliate programs

PR and Content

• Expert publications
• Webinars for agencies
• Success stories
• Educational materials

Support Program

• Training of agency employees
• Technical documentation
• Marketing materials
• Development consultations

Investments Required

• First seed round: $500,000
• Use: MVP development and marketing