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QuantaTrade AI — Technology Decisions

Decisions to Make Before Start

1. Blockchain Network

Option Pros Cons Recommendation
Ethereum L1 Most liquid, widest ecosystem High gas costs, slow Only for token listing, not daily ops
Base Low gas, Coinbase ecosystem, growing adoption Newer, less battle-tested Recommended for contracts
Arbitrum Low gas, mature L2, large DeFi ecosystem Competitive, many projects Good alternative
Solana Fast, cheap, growing institutional interest Different programming model (Rust) Only if client requires SPL token

Recommendation: Deploy $QTRA on Base (EVM-compatible, low gas, Coinbase alignment). Bridge to Ethereum L1 for exchange listings later.

2. Custody Provider

Option Notes
BitGo Confirmed by client (Richard-HFT, 2026-04-19). Multi-sig / TSS custody, institutional-grade, policy engine, approvals workflow.

Decision: BitGo. Earlier spec drafts listed Fireblocks — superseded by client's written confirmation on 2026-04-19.

3. KYC Provider

Option Pros Cons
Sumsub Used in QuantaTrade, proven integration, tiered KYC Cost per verification
Onfido Strong enterprise, good coverage More expensive
Jumio AI-powered, fast Less flexible

Recommendation: Sumsub — existing integration patterns from QuantaTrade, proven tiered KYC support.

4. Matching Engine

Option Pros Cons
Reuse exchange-core2 (Java) Already built, proven, fast Java dependency
Build new in Rust Better performance, modern Time to build from scratch
Build new in Go Good performance, simpler Less battle-tested for this use case

Recommendation: Reuse exchange-core2 with modifications. Already handles CLOB, order matching, risk checks. Saves 2-3 weeks of development.

5. Frontend Framework

Decision Choice Rationale
Framework Next.js 15 SSR, app router, React ecosystem
UI Library shadcn/ui + Tailwind Modern, customizable, fast
Charts TradingView Lightweight Charts Industry standard for trading
State Zustand + React Query Simple, performant
WebSocket Native WS + reconnect logic Real-time data

6. Backend Services

Decision Choice Rationale
API Framework NestJS (TypeScript) Modular, proven in QuantaTrade
Strategy Engine Python (FastAPI) ML ecosystem, pandas, numpy
Matching Engine Java (Spring Boot) Reuse exchange-core2
Database PostgreSQL 16 ACID, proven for ledger
Time-Series TimescaleDB Extension of PostgreSQL
Cache Redis 7 Cluster Pub/sub, order books
Message Broker Redpanda Kafka-compatible, simpler ops
Search Meilisearch Symbol search, news

7. Infrastructure

Decision Choice Rationale
Cloud GCP (or AWS) Depends on client preference
Container Orchestration Kubernetes (GKE) Production-grade scaling
CI/CD GitHub Actions + ArgoCD GitOps deployment
Monitoring Grafana + Prometheus + Loki Full observability stack
CDN Cloudflare WebSocket support, DDoS

8. Smart Contract Tooling

Decision Choice Rationale
Framework Hardhat Mature, good debugging
Language Solidity 0.8.x Standard for EVM
Libraries OpenZeppelin 5.x Audited, trusted
Testing Hardhat + Chai + ethers.js Standard toolchain
Audit Certik or Trail of Bits Required before mainnet