case · 007
Quantitative trading research platform.
A research-and-signal platform built for serious traders: a Next.js 15 dark-themed dashboard (TanStack Query, Recharts for financial charts, Zustand for client state) over a FastAPI backend with versioned Alembic migrations on SQLite → PostgreSQL. Phased delivery: data ingestion → signal engine → backtester → AI-assisted scoring.
fig. 0.1
Cover image · dashboard layout
Quantitative research lives or dies on reproducibility: same data slice, same strategy, same backtest result, every time.
Our team scoped and shipped the platform foundation: a Next.js 15 dark-themed front-end (TanStack Query v5 for server state, Zustand for client state, Recharts for financial charts, React Hook Form + Zod for forms) over a FastAPI async-first backend (SQLAlchemy 2.0, Alembic migrations, Pydantic v2, structlog). The dark trading theme is custom but starts from shadcn/Radix primitives so all controls are accessible by default.
phased deliverables, each independently shippable
Alembic migration chain (SQLite → PostgreSQL)
Recharts components in the operator dashboard
Alembic is wired from day one — no schema drift between dev and prod. SQLite for local iteration, PostgreSQL for prod with the same migration chain; alembic upgrade head works identically against either.
The roadmap is six phases: Phase 1 platform foundation, Phase 2 market-data ingestion, Phase 3 signal engine, Phase 4 backtesting engine with performance analytics, Phase 5 delivery via Telegram + subscriptions + billing, Phase 6 AI-assisted scoring. Each phase ships as a standalone capability that the previous one consumes — so the platform is useful on day one and grows linearly.
Async I/O throughout: uvicorn, async SQLAlchemy, async fetching — the front-end polls TanStack Query with no waterfall, and the operator dashboard renders live ticker state without re-fetching the page.
/ stack
- n/a — exchange read-only via Binance (extensible to other venues)
- Next.js 15 (App Router
- RSC)
- TypeScript strict
- Tailwind (dark trading theme)
- shadcn/ui
- TanStack Query v5
- Zustand
- Recharts
- React Hook Form + Zod
- Framer Motion
- FastAPI
- SQLAlchemy 2.0 (async)
- Alembic
- Pydantic v2
- structlog
- Uvicorn
next case study
Hybrid retrieval RAG pipeline..
A search engine that reads a folder of documents and answers natural-language questions in plain English, with citations pointing to the exact passage each fact came from. Combines ChromaDB dense retrieval with BM25 sparse retrieval via Reciprocal Rank Fusion (RRF), then re-ranks with a cross-encoder, then generates the answer with inline citations and a confidence score. Ships with a golden eval dataset and an evaluation harness that catches chunking/embedding regressions.
/ start a project