Project overview
FolioLytics turns brokerage and market feeds into a portfolio the user can read: value, allocation, performance and an AI layer that comments on the book — not on a random ticker.
Business challenge
Finance side-projects often stop at a chart. The useful system is identity, holdings sync, and insights that respect the actual book.
Solution architecture
Python for ingest and analysis. Next.js for the portfolio UI. Broker APIs for holdings. A constrained AI summary over computed metrics.
Ingest → normalize holdings → compute performance → optional AI narrative. The model does not invent positions.
Technology stack
Key features
Holdings sync
Broker-linked positions.
Performance & allocation
Value and mix the user can audit.
AI commentary
Narrative on computed metrics.
Modern web UI
Next.js, not a desktop terminal only.
My role
Implementation
Shows financial-data + AI + full-stack range next to the telecom portfolio. See also the FolioLytics blog note on this site.
Results / capabilities
- Feed-backed holdings
- Performance the user can check
- AI as commentary, not a black box book
Building something in this class?
Share the workflow, current stack and constraints. The first reply is an architecture-minded review.
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