added project goals documentation

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+ Vassal: 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.
+
+# Learning & Development Pillars
+
+While the end product is a functional utility, the development process is specifically designed to master the following domains:
+
+- Modern Spring Boot & Spring AI: Moving beyond basic CRUD to orchestrate complex AI workflows, utilizing the Spring AI ecosystem to handle prompts and structured outputs.
+
+- Vector Databases & Retrieval: Gaining hands-on experience in using vector databases in combination with classical development stacks.
+
+- System Architecture: Designing a "Bridge" architecture that is decoupled from the target application, allowing for a flexible, provider-agnostic middleware service.
+
+- AI Gateway Implementation: Mastering LiteLLM to manage multiple LLM providers (Gemini, OpenAI, Local LLMs).
+
+- Containerized Orchestration: Delivering a production-ready environment via Docker Compose that manages networked services (App, DB, Proxy) with a single command.
+
+# Product Goals (Public Value)
+
+Vassal 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").
+
+- Improve productivity: Reduce the time it takes to catalog physical items through AI-assisted batch processing.
+
+# Short-Term Roadmap & Milestones
+
+- 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.
+
+- Phase 2: The Processing Pipeline
+  * Implement the image processing workflow: Upload $\rightarrow$ AI analysis $\rightarrow$ staging Table.
+  * Develop the Next.js interface for data refinement and verification.
+
+- Phase 3: Semantic Search & Demo
+  * Integrate Spring AI for embedding generation.
+  * Launch a public-facing demo to showcase the full-stack solution.
+
+# Long-Term Roadmap & Milestones
+
+TBD