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**Vassal: Project Goals**
**Vaessl: Project Goals**
# Primary Objective
The goal of Vassal is to bridge the gap between unstructured physical data (images) and structured digital systems (Inventory APIs). This project serves as a technical deep-dive into the integration of Generative AI within a traditional Full-Stack Java/Spring Boot environment.
The goal of Vaessl is to bridge the gap between unstructured physical data (images) and structured digital systems (Inventory APIs). This project serves as a technical deep-dive into the integration of Generative AI within a traditional Full-Stack Java/Spring Boot environment.
# Learning & Development Pillars
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# Product Goals (Public Value)
Vassal is intended to be a useful tool for the public, specifically those utilizing self-hosted inventory systems like Homebox.
Vaessl is intended to be a useful tool for the public, specifically those utilizing self-hosted inventory systems like Homebox.
- Intuitive Discovery: Replace rigid keyword searches with intent-based search (e.g., finding a "Soldering Iron" when the user searches for "fix electronics").
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- Phase 1: Foundation (Current)
* Deploy the core infrastructure (PostgreSQL + pgvector, LiteLLM, Spring Boot Skeleton, Next.Js frontend).
* Establish the bridge between the Vassal backend and a demo Homebox instance.
* Establish the bridge between the Vaessl backend and a demo Homebox instance.
- Phase 2: The Processing Pipeline
* Implement the image processing workflow: Upload $\rightarrow$ AI analysis $\rightarrow$ staging Table.