CONVERGE
Stop scrolling strangers' reviews. Start following your taste twin.
A taste-based social network for going out. · 90,022 venues live across 9 cities in 5 countries.
The Problem
Going out is broken — no incumbent knows your taste
Yelp
Strangers' ratings
Shows what 100 anonymous reviewers clicked four stars — not what you'd love.
Google Maps
What's closest
Optimized for proximity and ads, not taste or a night out.
Instagram
Algorithmic popularity
Shows what's viral and who you already follow — not taste-matched discovery.
The Group Chat
Dies before you decide
Five tastes, zero decisions. Same five spots on rotation.
Recommendation quality is a behavioral-data problem, not a ratings problem.
The Solution
Three layers, one engine — live in the product
01
Build your taste
A five-step onboarding — city, board, taste scenes, mood, artists. We extract a 9-dimensional taste vector.
→ matched to you
02
Discover your taste twin
A feed and map of people whose vectors mathematically match yours. Follow, save, share.
→ people, not places
03
Plan a night in 60s
Private inputs → a group composite → three identity-coded itineraries. Vote. Ship.
→ an answer becomes a plan
The unifying primitive is the taste vector. Every swipe, follow, plan, and vote sharpens it.
Why It's Defensible
A behavioral data flywheel
The Flywheel
1
Swipes, saves, follows, real outings
2
A 9-dimensional taste vector per user
3
Cluster discovery — mathematically similar people
4
Follow / save / share with your taste twin
5
More data → sharper vectors → repeat
Why incumbents can't replicate
Yelp / Google
Unit economics are venue advertising, not social-graph density.
Instagram / TikTok
Optimizes for content engagement, not local taste discovery.
Resy / OpenTable
Transactional booking — no behavioral taste-data layer.
By the time an incumbent pivots to a taste graph, the data lead compounds against them.
Market
A big backdrop — but we size what we can capture
$0T
US dining-out industry (TAM)
Context, not our revenue.
$0B
Serviceable market (SAM)
Discovery-influenced local spend.
~$0K
Revenue per mature city / yr
Bottoms-up, illustrative.
~10 cities ≈ $8M ARR · ~30 cities ≈ $24M ARR (core engines). We never sum engines into one TAM.
Traction & Roadmap
Shipped and in production — scaling by design
0
venues & events, 9 cities · 5 countries
9-D
taste-vector engine, live
0+
API endpoints · app live on iOS
Early proof — small-scale, pre-marketing
Honest status: pre-user-scale. The engine and the inventory are built; the demand side is the work ahead.
Strategic Beachhead
Why Howard, why now
01
Founder is in the cohort
A Howard finance senior building for how Howard students actually plan nights — inside-out, not an outsider's bet.
02
HBCU density compounds
Tightly-connected social graphs bootstrap the taste flywheel faster from a dense, high-trust cohort.
03
HBCU campuses set culture
Howard's scene shapes taste far beyond its walls — Hampton, Spelman, Morehouse, then beyond.
Beachhead: Howard, August 2026 · UCLA follows in September.
Business Model
One engine, four ways to earn
Live
Consumer affiliate
Ticketmaster, Viator, OpenTable on bookings — wired in production.
Live
B2B venue data
Cluster-save analytics + labeled "Promoted" placement. The lead engine.
Near
Seasonal sponsorship
Brand activations tied to local moments and campus seasons.
Later
Artist agency
Taste-layer for artists — booking & management on venue relationships.
Monetize the supply side — never the taste signal. No pay-to-rank; sponsored is firewalled from organic discovery.
Team & Advisors
Operators with the exact edges this needs
JK
Jared Keys
Founder & CEO
Howard finance senior; product, strategy, and the AI-assisted codebase.
LD
Lead Developer
In seat since May 2026
Software/SaaS + computer vision. Owns the React Native app + backend. Name shared in diligence.
TB
Talia Balogun
Head of Growth
Acquisition, campus operations, and the student rep program.
CK
Craig Keys
Advisor · Live Nation SVP
Music/nightlife: A&R, venue & talent relationships. (Related-party governed.)
Why Now
The AI-enabled founder advantage
60–80% cost compression
AI engineering vs. a 2022 consumer-app build — a production stack a small team can own.
Interface unbundling
The knowledge front door is shifting from search to AI chat — attention and habit are up for grabs.
In-person demand peak
Loneliness at public-health levels; a generation craving real connection over more screen time.
The Ask
Pre-seed round
$0K
Post-money SAFE · $5M valuation cap
Illustrative pre-seed terms — ~10% at close.
Milestones this raise funds
First paying venue accounts
5 HBCU campuses in the network
First sponsored activation live
Validated city-one density economics
Closing Vision
The taste-data layer for a generation.
Howard first. Then every HBCU. Then every city.
The product is live — web and the App Store. The flywheel is seeding. Converge optimizes for going.