A social discovery platform powered by AI recommendation

Joyraft's users missed good events when they appeared below the fold, and a small team could not keep three native apps in step. Twistag built iOS, Android and web from one shared codebase, and a Vertex AI recommendation engine that weights what friends are doing. Joyraft reached more than 10,000 weekly active users, and over 40% of clicks go to events outside the top three positions.

  • Joyraft
  • Software & platforms
  • AI & Agents
  • Product Engineering
Friends walking towards an outdoor event at dusk under string lights
  • 10K+weekly active users
  • 40%+of clicks on events outside the top three positions
  • 3platforms from one shared codebase
Client
Joyraft
Industry
Software & platforms
Practices
AI & Agents, Product Engineering
Timeline
Multi-year, ongoing
Stack
React Native, Next.js, Vertex AI, GCP
Discuss a similar case
The challenge

Good matches, never seen.

Twistag built Joyraft, an AI-powered social event discovery app running on iOS, Android and web from a shared codebase, which reached 10,000-plus weekly active users with a recommendation engine that drives 40%-plus of clicks on events placed outside the top of the feed. Joyraft's problem was that good event matches went unseen when they fell below the fold. Twistag built React Native for mobile and Next.js for web behind a shared component library, and a hybrid recommendation engine on Google Cloud's Vertex AI combining collaborative filtering with content signals — then weighted friend activity above algorithmic confidence, because user testing showed social proof outperforms prediction.

Event discovery on mobile has a hard problem: users do not know what they are looking for, and recommendations that miss get ignored. Joyraft's founding team saw it directly in user research — when events were buried below the fold, even strong matches failed to convert because users never saw them. The discovery experience itself had become the bottleneck. The second constraint was structural. Joyraft needed to reach users across iOS, Android and web, and building three native applications meant tripling the work: design consistency broke down, feature releases staggered, and a small team could not ship fast enough to iterate on the AI layer at all. The business needed to grow and the platform could not scale with the team size.

The approach

Friends first, then the model.

  1. One codebase, three apps.

    React Native for iOS and Android and Next.js for web, joined by a shared component library, so a six-person team ships each feature once.

  2. Hybrid recommendations.

    Vertex AI combines what similar users engaged with and each event's details, and takes in new signals as soon as someone marks interest.

  3. Social proof leads.

    User testing showed that friends' activity drives engagement, so it ranks alongside the model's confidence.

  4. Data before the model.

    The app launched without recommendations and introduced them gradually, once there was real behaviour to learn from.

The impact

Recommendations people trust.

Joyraft reached 10,000-plus weekly active users across iOS, Android and web. The recommendation engine drives 40%-plus of clicks on recommended events that fall outside the top three positions in the feed — users engage with recommendations even when the algorithm places them low, which is the signal that users trust the matching logic. Feature parity across the three platforms eliminated the release stagger that defeats most small multi-platform teams: one release cycle, one design system, three experiences that feel identical. That trust is the only durable form of discovery.

Forty percent of clicks land outside the top three — the engine works quietly.

  • React Native
  • Next.js
  • Vertex AI
  • GCP
Twistag built Joyraft, an AI social event discovery app on iOS, Android and web that reached more than 10,000 weekly active users.
Have a similar challenge?

Start with the work that should change first.

A thirty-minute call, then a one-page outline of how Twistag would approach it.

A senior lead replies within one working day.

Talk to us

Tell us where work gets stuck.

A senior engineer replies within one working day.

Interested in

Thirty-minute call

Pick a time.