Allen Wang
CEO
Ditto
Ditto uses a large‑language model and specialized AI agents to generate a single high‑compatibility match for each student each week, based on verified campus profiles. The service automates scheduling, selects vetted on‑campus coffee venues, and delivers match details and conversation tips via SMS, eliminating in‑app messaging. Students access the matches through a subscription or pay‑as‑you‑go model, receiving a private, low‑effort opportunity for in‑person socializing.
Traction 5/10Founded 2024
Berkeley, United States · HQ
- Artificial Intelligence
- AI Agents
- Applications
- Social Networking
- Software Only
Updated 3 days ago
Funding
Raised to date
$1.6MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Funding rounds are not available yet.
Founders
Product
Problem
College students often struggle to find safe, low‑friction opportunities for in‑person social interaction on campus, especially when traditional dating apps require extensive swiping, messaging, and verification processes that can feel invasive or time‑consuming.
Solution
Ditto leverages a frontier large‑language model combined with a suite of specialized AI agents to analyze verified student profiles and generate a single, high‑compatibility match each week. After profile submission, the system automatically produces a personalized match poster, synchronizes both users’ availability through a scheduling agent, and delivers a complete date plan—including time, location, and brief conversation tips—via SMS. All interactions remain private: only the two matched students see each other’s details, and the matchmaking process runs without any public swiping or chat interface. The service operates on a weekly cadence, ensuring that users receive a curated on‑campus coffee date within 48 hours of signing up for most participants. Continuous feedback loops allow users to reject a match and trigger an immediate re‑match, improving relevance over time.
Target Audience
The primary customers are undergraduate and graduate students at accredited universities who seek convenient, vetted, and low‑effort opportunities for in‑person socializing on campus.
Features
- End‑to‑end AI pipeline: profile parsing, preference modeling, and compatibility scoring using a large‑language model and domain‑specific matchmaking agents.
- Automated scheduling agent that aggregates both participants’ weekly availability and proposes optimal meeting times.
- SMS‑based delivery of match posters, location details, and date‑specific etiquette tips, eliminating the need for in‑app messaging.
- Campus‑centric venue selection algorithm that selects vetted, low‑traffic coffee spots to maximize safety and convenience.
- Real‑time feedback handling that retriggers the matchmaking workflow when a user declines a match or updates preferences.
- Verification layer that restricts the pool to enrolled students aged 18 + and enforces privacy by limiting profile visibility to the matched pair.
- Scalable cloud infrastructure with secure data storage and compliance with standard student privacy regulations.