RevOpsXL Lettore wanted a reading app people came back to. RevOps XL built the AI core and the full backend, then wired the activation and retention loops that turn a first session into a habit.
Reading habit apps live or die on whether a user opens them tomorrow. Lettore came in with a clear product vision and zero infrastructure. They needed an AI layer that personalised recommendations without feeling generic, and a backend that could carry the product through scale. The onboarding and retention loops had to turn signups into a habit by week four.
The personalisation and recommendation engine sits at the centre of the experience. Recommendations get sharper every session and surface the right book at the right moment, without sliding into a generic feed. Under the ranking, the AI holds a model of what kind of reader you are.
Data model, services, APIs, the lot. We built the backend as a long-term asset rather than something rushed out to hit a ship date. Identity, content, reading state, and behavioural signal each sit in their own clean layer. Everything the team needs to ship the next ten features is there.
First session: discover three books in under 60 seconds. First week: build a reading streak that the AI rewards. Month two: the habit runs itself. We mapped the loop end-to-end and instrumented it, then built the product around it.
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40 hours of senior practitioner work. Read-only access. Full documentation, 90-day roadmap, 2-hour walkthrough. Whether you keep RevOps XL on or not is your call.