AI Book Recommendation Automation
A personalized recommendation workflow for aisr.qa that combines user job data with an AI interview. It returns eight role-relevant book picks, making recommendations feel curated without manual research.
n8n
OpenAI APIThe challenge
Client challenge
aisr.qa needed a scalable way to deliver personalized book recommendations based on each user's job role and goals — without a manual curation process that couldn't scale to their growing user base.
The build
What I built
I built an n8n automation that queries the user database for professional context, conducts an AI-powered conversational interview to surface goals and challenges, and returns 8 curated book recommendations precisely matched to each user.
- Automated user data query from the database
- AI conversational interview pipeline via n8n
- Context-aware book recommendation generation
- 8 tailored recommendations per user per run
- Webhook-triggered delivery on user request
The outcome
Measured outcomes
Every user receives fully personalized recommendations at scale with zero manual curation. The AI interview step grounds recommendations in each user's actual situation — going far beyond job title to deliver genuinely relevant results.
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