Recapy
Recapy is a mobile-first PWA that turns trending story questions into focused AI recaps for TV, movies, and books — helping users catch up before the next episode, season, or chapter.
- Timeline
- 14 weeks from MVP to public catalog with monetization
- Role
- Product design, AI pipeline architecture, full-stack development, and SEO content strategy
The challenge
Entertainment audiences constantly fall behind — a friend mentions a plot twist, a new season drops, or a book club picks a title nobody has finished. Existing recap content is scattered across wikis, forums, and spoiler-heavy videos with no consistent quality or mobile experience. The team wanted to capture real search intent around "what happened in…" queries and deliver concise, accurate recaps powered by AI without sacrificing trust or readability.
Our approach
We built Recapy around two surfaces: a public SEO catalog that ranks for high-intent entertainment queries, and an authenticated experience for users who want personalised follow-ups. The AI recap engine uses retrieval-augmented context to ground summaries in verified plot data rather than hallucinating details. A trend sync pipeline pulls signals from TMDB and NYT bestseller lists so new recap pages publish while topics are still rising, not after the moment passes.
The solution
Recapy ships as a unified Next.js application covering marketing pages, the public recap catalog, authenticated user library, API layer, auth, and AI orchestration. Each recap page is structured for search engines and mobile reading — short enough to scan before a commute, deep enough to answer "what did I miss?" Signed-in users save titles, upload notes, and ask follow-up questions with personal context layered on top of the base recap. Monetization surfaces integrate without breaking the reading flow, and the PWA install path gives repeat users app-like access from their home screen.
Outcomes
Public recap pages drove organic traffic by matching content to real search patterns around TV, film, and books. Users spent more time on pages with interactive follow-up Q&A compared to static summaries alone. The trend sync pipeline kept the catalog fresh without manual editorial overhead, and the authenticated library turned one-time visitors into returning readers ahead of each new episode or chapter.
Key outcomes
- Organic traffic growth from intent-matched recap pages
- Stronger session engagement on public recap pages with follow-up Q&A
- Trend sync from TMDB and bestseller lists kept the catalog aligned with what people were searching for
- Authenticated users could save titles and ask contextual follow-up questions from their library