AI Assistant Backend Development for Comic Book App
Sergei Serafimovich
Context
The application allows users to manage their comic book collections, but users often want deeper insights: recommendations aligned with their taste, answers about authors or storylines, and contextual knowledge about characters and first appearances. The goal was to build an AI assistant backend that could power these features reliably and at scale.
What Was Built
I developed the backend for an AI assistant based on Gemini, designed to integrate deeply with application data and deliver accurate, personalized responses.
The assistant can:
Recommend comics aligned with user's reading preferences
Answer detailed questions about comics, authors, plots, and characters
Adapt responses based on the user’s collection, wishlist, and reading profile
How It Works
LLM + Tools-Based Generation
The LLM uses its own knowledge together with application tools to generate a response.
Available tools provide access to:
the user’s collection
the wishlist
a precomputed and cached reader profile (preferred genres, authors, styles)
Verification & Enrichment
The generated response is verified to reduce hallucinations and factual errors.
In parallel, all referenced comics are enriched with metadata from the database (titles, covers, publication data, links).
Structured Output
The final response is returned as structured data, allowing the frontend to render mentioned comics as rich blocks with full details and navigation links.
Results & Benefits
Highly personalized AI-driven features without hardcoding business logic into the frontend
Reliable answers grounded in both model knowledge and application data
A scalable backend architecture that can evolve with new tools and data sources
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Posted Dec 19, 2025
Developed AI assistant backend for comic book app with personalized features.
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Timeline
Feb 10, 2025 - Mar 12, 2025
