Selfany AI Pairing 🤖

Selfany AI Pairing 🤖

Help subscribers, students, space members, or event ticket holders connect with the most suitable person based on their profile, interests, goals, availability, and responses.

The tool uses AI to recommend compatible pairings while giving the admin full control to manually review and approve each match before it becomes active.

Once a pairing is approved, both members get access to a private chat room where they can connect, interact, and continue the conversation.

 

How AI Pairing on Selfany Works

The AI would assess each completed subscriber, member, or event ticket holder profile using a mix of compatibility, goals, availability, personality, and admin-defined rules. The goal is not just to match people randomly, but to recommend pairings that are likely to create meaningful conversations, useful support, and productive connections.

1. Profile Completion

The AI should first check whether both users have completed the required pairing profile fields.

Details to consider:

• Full name or display name

• Short bio or personal introduction

• Location

• Time zone

• Language preference

• Industry, niche, or area of interest

• Role or identity within the space

• Reason for joining the space, event, or community

• Consent to be considered for pairing

The AI should only recommend users who have completed the required pairing profile and opted in to be paired.

2. Goals and Intent

The AI should compare what each person wants to achieve.

Details to consider:

• Main goal for joining the space

• Personal or professional objective

• What they hope to gain from being paired

• Whether they want accountability, mentorship, collaboration, friendship, networking, support, learning, or business growth

• Short-term goals

• Long-term goals

• Specific outcomes they want from the pairing

Example:
A member looking for weekly accountability should be paired with someone who also wants structure, consistency, and regular check-ins.

3. Interests and Topics

The AI should identify shared or complementary interests.

Details to consider:

• Common topics of interest

• Shared industries or niches

• Similar learning interests

• Similar event/session interests

• Products, services, or skills they are interested in

• Communities or categories they belong to inside the space

• Preferred discussion topics

Example:
If two event attendees both selected “business growth,” “content creation,” and “monetization,” the AI can consider them a stronger match.

4. Experience Level

The AI should assess whether users are at similar or complementary stages.

Details to consider:

• Beginner, intermediate, or advanced level

• Years of experience

• Current stage of business, career, faith journey, learning journey, or personal development journey

• Whether the person wants to connect with someone at the same level

• Whether the person prefers someone more experienced

• Whether the person is open to supporting someone less experienced

Possible pairing styles:

• Peer-to-peer pairing

• Beginner with beginner

• Advanced with advanced

• Mentor-style pairing

• Experienced member with newer member

• Complementary skill pairing

5. Availability and Time Zone

The AI should check whether both users can realistically connect.

Details to consider:

• Country

• City

• Time zone

• Preferred meeting days

• Preferred meeting times

• Frequency of communication

• Availability during the event or programme

• Whether they prefer weekday or weekend conversations

• Whether they can connect across time zones

Example:
A strong profile match may still be a poor pairing if one person is only available in the morning and the other is only available late at night.

6. Communication Preference

The AI should assess how each user prefers to connect.

Details to consider:

• Chat only

• Voice notes

• Audio calls

• Video calls

• In-person meetups, where relevant

• Weekly check-ins

• Daily check-ins

• Casual conversations

• Structured conversations

• Formal or informal communication style

Example:
Someone who wants casual chat may not be the best match for someone who wants strict weekly accountability calls.

7. Personality and Interaction Style

The AI should consider how people describe themselves and how they prefer to engage.

Details to consider:

• Introverted or extroverted

• Quiet or expressive

• Structured or flexible

• Motivational or reflective

• Fast-paced or slow-paced

• Direct or gentle communication preference

• Preference for deep conversations or light conversations

• Need for encouragement, challenge, or accountability

Example:
Someone who wants a highly disciplined accountability partner may be better matched with someone structured and consistent.

8. Values and Expectations

The AI should compare what each person values in a pairing.

Details to consider:

• Honesty

• Respect

• Consistency

• Confidentiality

• Growth mindset

• Faith or belief alignment, where relevant

• Professionalism

• Openness

• Collaboration

• Seriousness of intent

Example:
If one person says confidentiality is very important and another says they value deep private conversations, that may increase compatibility.

9. Pairing Purpose

The AI should understand the type of pairing the admin wants to create.

Details to consider:

• Accountability partner

• Study partner

• Prayer partner

• Business partner

• Networking match

• Event buddy

• Mastermind partner

• Mentorship match

• Collaboration partner

• Peer support partner

• Community engagement partner

The admin should be able to choose the pairing purpose before AI recommendations are generated.

10. Compatibility Score

The AI should generate a compatibility score for every recommended pair.

Suggested scoring areas:

• Goal alignment

• Interest alignment

• Availability match

• Communication preference match

• Experience-level fit

• Personality compatibility

• Location or time zone fit

• Admin rule compliance

• Mutual expectations

• Risk or mismatch level

Example:
Overall Match Score: 86%

Breakdown:

• Goals: 92%

• Interests: 88%

• Availability: 80%

• Communication Style: 85%

• Experience Fit: 83%

• Time Zone Fit: 90%

11. Why This Pairing May Work

The AI should explain each recommendation in simple language so the admin can make a good decision.

The explanation should include:

• What both users have in common

• Why their goals align

• How their availability matches

• Why their personalities or communication styles may work

• What each person may gain from the pairing

• Any complementary strengths

Example:
This pairing may work because both members are focused on business growth, prefer weekly check-ins, are available on weekday evenings, and want an accountability partner who can help them stay consistent.

12. Possible Concerns or Mismatch Flags

The AI should also show possible concerns before the admin approves the pairing.

Details to flag:

• Conflicting availability

• Different time zones

• Different expectations

• Different communication preferences

• One person wants mentorship while the other wants peer support

• One person prefers same-country pairing while the other is international

• One person wants frequent communication while the other prefers occasional check-ins

• Sensitive preference conflicts

• Incomplete or unclear profile answers

Example:
Possible concern: Sarah prefers video calls, while Tolu selected chat-only communication.

13. Admin-Defined Rules

The AI should follow rules set by the space owner or admin.

Admin should be able to define:

• Pair only people in the same cohort

• Pair only people in the same event

• Pair only people who bought the same ticket type

• Pair by gender, where appropriate and lawful

• Pair by location or country

• Pair by time zone

• Pair by language

• Pair beginners with advanced members

• Pair people with similar goals

• Avoid pairing people from the same company

• Avoid pairing people who have already been paired before

• Do not repeat old pairings

• Limit each user to one active pairing

• Allow multiple pairings per user

• Create pairings manually only after AI suggestion

14. Ticket or Access Type

For event-based pairing, the AI should consider ticket type and access level.

Details to consider:

• Ticket purchased

• Event attended

• Session selected

• VIP or general ticket

• Workshop track

• Breakout room interest

• Paid or free participant

• Cohort or batch

• Attendance status

• Event location, online or physical

Example:
VIP ticket holders may be paired with other VIP ticket holders if the admin wants to preserve access-level relevance.

15. Space Activity and Engagement

The AI can consider how active each person is inside the space.

Details to consider:

• Login activity

• Content completed

• Sessions attended

• Comments or community participation

• Messages sent in public space

• Assignments submitted

• Event attendance

• Profile freshness

• Responsiveness

Example:
A highly active member may be better paired with another active member to avoid frustration.

16. Pairing History

The AI should check previous pairing records before recommending a new match.

Details to consider:

• Has this user been paired before?

• Who were they previously paired with?

• Was the previous pairing successful?

• Did they request a new pairing?

• Did they report or block someone?

• Did the admin dissolve a previous pairing?

• Was there positive or negative feedback?

• Should this user be excluded temporarily?

17. Feedback From Previous Pairings

If the tool supports recurring pairing, the AI should learn from past feedback.

Details to consider:

• Pairing rating

• Feedback from both members

• Reason for ending pairing

• Communication frequency

• Reported issues

• Successful check-ins

• Goal completion

• Admin notes

Example:
If a user previously gave feedback that they prefer someone more structured, the AI should consider that in the next recommendation.

18. Safety and Privacy

The AI should avoid unsafe or inappropriate pairings.

Details to consider:

• Blocked users

• Reported users

• Admin-restricted users

• Users removed from pairing

• Users who opted out

• Sensitive profile conflicts

• Age-related restrictions, where relevant

• Privacy preferences

• Visibility settings

The AI should never expose private profile answers to another user unless the platform clearly states that those answers will be shared.

19. Profile Visibility

The AI should distinguish between admin-only answers and partner-visible answers.

Profile answers can be grouped as:

• Used only for AI matching

• Visible only to admin

• Visible to approved partner

• Hidden from other members

Example:
A member’s goals and bio may be visible to their approved partner, but private preferences or sensitive answers should remain admin-only.

20. Recommended Pairing Output

For every recommended pair, the AI should produce a clear recommendation card.

The card should include:

• Member A

• Member B

• Match score

• Pairing type

• Why this pairing may work

• Shared interests

• Shared goals

• Availability match

• Communication match

• Possible concerns

• Recommended first conversation prompt

• Admin action buttons

Admin actions:

• Approve pairing

• Reject pairing

• View both profiles

• Ask AI for another recommendation

• Replace one member

• Create pairing manually

• Add admin note

21. Private Chat Room Setup

Once pairing is approved, the AI/system should prepare the private room.

The private room may include:

• Private chat

• Partner profile summary

• Suggested icebreakers

• Shared goals section

• Check-in prompts

• Notes section

• File sharing, if enabled

• Meeting link section

• Report or request new pairing button

Suggested first prompts:

• What made you join this space?

• What are your top three goals?

• How would you like us to support each other?

• How often should we check in?

• What would make this pairing successful?

• What are you currently working on?

• What kind of accountability do you need?

22. Re-Pairing Rules

The AI should support re-pairing when needed.

Details to consider:

• Member requested a new partner

• Pairing became inactive

• One member left the space

• One member stopped responding

• Admin dissolved the pairing

• Pairing duration ended

• Event ended and follow-up pairing is needed

The admin should be able to approve any re-pairing before the new chat room becomes active.

23. Matching Weight

The admin should be able to decide what matters most.

Example weighting:

• Goals: 30%

• Availability: 20%

• Interests: 20%

• Communication preference: 10%

• Experience level: 10%

• Location/time zone: 5%

• Personality/style: 5%

For an event:

• Ticket type/session interest: 25%

• Goals: 25%

• Availability: 15%

• Interests: 15%

• Location: 10%

• Communication preference: 10%

For a mentorship space:

• Experience level: 30%

• Goals: 25%

• Industry/niche: 20%

• Availability: 15%

• Communication style: 10%

24. Important AI Rule

The AI should recommend pairings, not activate them automatically, unless the admin enables auto-approval.

Default rule:
AI recommends. Admin reviews. Admin approves. Pairing becomes active. Private chat room opens.

25. Ideal Pairing Summary

The ideal pairing should answer these questions:

• Are these two people looking for similar or complementary outcomes?

• Can they realistically connect based on availability?

• Do their communication preferences align?

• Is there enough shared interest to start a conversation?

• Is there enough difference for them to add value to each other?

• Are there any concerns the admin should review first?

• Will this pairing likely help both members get more value from the space or event?

You can use this as the product logic for your AI pairing tool.