NXRISEUP
A trading journal and analysis platform that turns raw trade history into reviewable performance decisions — trade log, sessions and alerts, market signals, and AI-powered trade analysis.
ORGANIZATION
INDEPENDENT PRODUCT
PERIOD
2025 — PRESENT
ROLE
DESIGN · BUILD · SHIP — SOLO
STACK
NEXT.JS · RECHARTS · GEMINI API
01 — THE BRIEF
Traders accumulate history — entries, exits, sessions, outcomes — but raw logs don't answer the only question that matters: what should I do differently? NXRiseUp is built around that gap.
The platform ingests trades (including straight from Excel), organizes them into sessions with alerts and market signals, and layers AI analysis on top so a trader reviews decisions, not rows.
02 — OPERATING CONSTRAINTS
- Trade data arrives messy — Excel import has to tolerate real-world files, not ideal ones.
- Analysis must be reviewable: charts and signals a trader can interrogate, not a black-box score.
- Solo build: product strategy, data model, UI, AI integration, and deployment by one engineer.
03 — SYSTEM STRUCTURE
NEXT.JS APP
Trade log, session management, alerts, and market-signal views.
RECHARTS ANALYTICS
Performance visualizations that make patterns in the trade history visible.
EXCEL IMPORT PATH
Existing trade history flows in from spreadsheets — no manual re-entry.
GEMINI AI ANALYSIS
AI-powered trade analysis over the journal — from raw history to reviewable read-outs.
04 — KEY DECISIONS
DECISION 01
Journal first, AI second
The AI layer is only as good as the data under it — the product makes clean, structured trade history the foundation, then lets AI interpret it.
DECISION 02
Meet traders where their data lives
Excel import was a launch feature, not an afterthought — adoption dies at 'please re-enter your trades'.
DECISION 03
Ship live, iterate in public
The product is deployed and clickable — evidence beats description.
05 — OUTCOME
Raw trade history becomes reviewable performance decisions.
- · Live and public — open it, click around, judge the craft directly.
- · Same pattern as the enterprise work: capture data, clean it, model it, ship an interface a decision-maker can act from.
CROSS-EXAMINATION
The full walkthrough — code, schema, trade-offs — happens live. Fifteen minutes, no slides.
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