Meetwise.ai

a solution to the last-mile problem in social & networking settings

A location-based, LLM-powered, multi-profile networking app that fosters high-quality in-person connection

Problem Statement

People feel not efficient enough in identifying the right people to interact & connect with when they attend in-person networking / social events.

User Research

Demograph

  • Age group: 18-34 (67.5%), 35-54 (30%)

  • Gender: Female (70%), Male (27.5%), other (2.5%)

  • Status: Married (42.5%), Not Married (57.5%)

  • Occupation: Student, Business Professional, Technical Professional, Entrepreneur, Homemaker

Networking Event

  • 70% attend networking events / social gatherings at least once a month

  • 92% want to establish meaning connections at these events

  • Most used methods are “social media platforms” (57.5%) and “directly talk to people nearby” (67.5%)

  • 90% feels a certain degree of inefficiency in identifying the right people to connect with at these events

77.5% finds value in a service to address this inefficiency problem

Solution - core product concept

Step 0

Messages are based on sessions and personas

Step 1

Sophia created 2 personas: professional and social.

Step 5

Sophia gets alert that an invite is accept / have received a new invite

Figma Prototype

User Journey - Sophia

Step 2

Sophia reviews her summary tags, and update (via voice / typing) her professional profile using LLM. She also informs her agent to look for hiring opportunities.

Step 3

When Sophia arrives at a conference, she starts a session to make her profile visible.

Step 4

Sophia gets recommendations based on her interest and needs. Send out invite to chat.

Step 6

Start conversation with the person you invited, and confirm commitment

Step 7

Ice-breaker topics are offered based on the 2 profiles

Step 8

End sessions when you are done

Further Discussions

  • Building an app that involves sensitive data such as personal profiles can indeed raise valid privacy concerns. Here are the steps we might consider to address this concern:

    • Anonymize personally identifiable information (PII) such as names, addresses, phone numbers, etc., before sending data for processing.

    • User Consent & Transparency: Before users interact with the app, inform them about what data will be used and how it will be processed.

    • Data Retention Policy: all data will be kept for a time range specified by the user.

    • Feedback Loop: a channel is provided for users to raise concerns or report any anomalies they notice.

  • Safe Meeting Protocols:

    • Event-specific usage: Collaborate with event hosts so that only people attending the same official event will be able to make profile visible to each other.

    • Safe Locations: Suggest or highlight public places for first meetings.

    • Emergency Check-ins: users can notify a trusted contact about their meeting location and check-in at set intervals.

    • Safety Tips: Offer safety guidelines and tips for users meeting someone for the first time.

    • Report & Block: Implement a robust system for users to report inappropriate behavior or content and block other users.

  • Channel partnerships

    • conferences & networking events

    • music festivals and large social gatherings

    • daycare centers and schools

    • etc.

Product Pub Design Sprint

Product Pub Design Sprint

This project was developed in 2023/7 at product pub design sprint event at Sillicon Vally, winning the “Dream Big” prize with my awesome teammates:

Dylan Yang (@Accenture), Lan Y. (@Walmart), Aiden Cai (entrepreneur), Tiankun Lu (@Google)

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Virtual City Project - 2023