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.
Funding
$1.6M raised to dateRaised 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.
Founders
Product
Problem
College students often struggle to find safe, reliable, and convenient ways to meet peers for dates, especially on campus where concerns about authenticity and personal safety are high. Traditional dating apps require extensive swiping, messaging, and verification, leading to wasted time and potential exposure to unverified users.
Solution
Ditt uses advanced large‑language‑model reasoning and a suite of specialized AI agents to match verified college students based on their profiles and stated preferences. After a user submits their information, the system generates a curated date plan—including time, location, and a brief match rationale—and delivers it via text. An integrated scheduler collects availability from both parties, automatically finalizing the date details and providing personalized tips. If a match is unsatisfactory, users can give feedback, prompting Ditt to generate a new, improved pairing without additional effort. All interactions occur through campus‑approved locations to maintain safety and privacy.
Target Audience
The service is aimed at college students aged 18 and older who seek a secure, low‑effort way to meet fellow students for in‑person coffee dates on or near their campus.
Features
- AI‑driven profile analysis and preference matching using frontier LLMs for high‑quality pairings
- Automated text‑based delivery of match information, including photos, match rationale, and date itinerary
- Built‑in scheduling assistant that aggregates both users’ weekly availability and confirms a mutually convenient time
- Real‑time safety safeguards: only verified students (18+) are eligible, and dates are limited to vetted on‑campus venues
- Feedback loop that lets users reject a match and receive a new recommendation based on their input
- Agentic system coordinating expert modules for matchmaking, poster creation, scheduling, and dating‑tip generation