F1 Performance Intelligence Platform

Unified multi-discipline engineering platform for the Apex Racing F1 team — real-time telemetry ingestion, strategic analytics, low-code dashboards, DevOps, and AI-powered race engineering.

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Overview

Built for race engineers, strategists, and DevOps teams who need instant visibility into car performance, infrastructure health, and race-weekend operations. Simulates a production-grade data pipeline (Kafka → Spark → Snowflake) with live WebSocket telemetry streaming and an AI Race Engineer assistant powered by Groq.

Features

Telemetry & Analytics

• Live Telemetry Viewer — Real-time 10Hz multi-driver telemetry overlay with channel comparison and diff diagnosis
• Delta-P Analysis — Lap-by-lap delta vs rival drivers with sector heatmaps and trend visualization
• Tire Degradation Curves — Compound-specific degradation modeling with cliff detection
• Fuel Trends — Consumption tracking with fuel-corrected lap time normalization
• Session Comparison — Head-to-head driver/session analysis with engineer leaderboard

Strategy & Race Ops

• Pit-Stop Window Planner — Optimal pit window Gantt chart with compound-specific strategies
• Tire-Age Projection — Cliff-lap prediction for soft/medium/hard compounds with live indicator
• Undercut Simulator — Interactive pit-lap optimizer with out-lap pace adjustment
• Race Ops Dashboard — Pipeline health monitoring, incident playbooks, synthetic race simulation

AI Race Engineer

• LLM-Powered Assistant — Ask natural language questions about telemetry anomalies, setup changes, and race strategy
• Live Context — Automatically injects active alerts, session laps, delta-P, and channel diffs into prompts
• Data-Driven Recommendations — References specific corners, sectors, and channel values

Low-Code Builder

• Drag-and-Drop Dashboard Builder — SQL templates onto a canvas with 5 visualization types
• Parameterized SQL — Session and driver selectors auto-fill query parameters

DevOps & Operations

• CI/CD Pipeline Visualization — 7-stage pipeline with simulated canary progression
• Canary Rollback — One-click rollback with automated incident logging
• Audit Log — Full activity trail across playbooks, deploys, AI queries, and template runs

Platform

• Command Palette — ⌘K quick-access to any view, session, or action
• PDF Report Generation — Session-specific reports with driver comparison and recommendations
• Mobile Pit-Box View — Touch-optimized compact dashboard for iPad

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Tech Stack

Layer	Technology
Framework	Next.js 16 (App Router)
Language	TypeScript 5 (strict mode)
Styling	Tailwind CSS 4, shadcn/ui
Database	Prisma + SQLite
Charts	Recharts
State	Zustand
Real-time	WebSocket via Caddy gateway
Animation	Framer Motion
AI	Groq API (qwen3.8-27b)
PDF	Python ReportLab

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Getting Started

Prerequisites

• Bun >= 1.2 or Node.js >= 20
• Python 3.10+ (for PDF generation)

Setup

git clone https://github.com/hemv-857/f1-performance-intelligence.git
cd f1-performance-intelligence

bun install
bunx prisma generate
bunx prisma db push
bunx tsx prisma/seed.ts

bun run dev

Open http://localhost:3000.

Environment Variables

Copy .env.example to .env:

DATABASE_URL=file:./db/custom.db
AI_API_URL=https://api.groq.com/openai/v1/chat/completions
AI_API_KEY=your-groq-api-key
AI_MODEL=qwen/qwen3.8-27b

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Database Schema

Model	Purpose
Driver	10 drivers (6 Apex Racing + 4 rivals)
Circuit	8 circuits (Suzuka, Singapore, Austin, Monaco, Silverstone, Spa, Monza, Zandvoort)
Channel	14 telemetry channels
Session	40 sessions across 3 seasons
Lap	~2000 laps with sector times, tire compound, fuel load
TelemetrySample	~524k samples at 10Hz
DeltaRecord	~7000 delta-P records vs rivals
Deployment	CI/CD deployment history
Alert	System alerts
DashboardTemplate	6 low-code SQL templates
IncidentRun	Playbook execution history
AuditLog	Full activity audit trail

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Project Structure

src/
├── app/                    # Next.js App Router
│   ├── api/                # API routes (21 endpoints)
│   └── layout.tsx          # Root layout
├── components/
│   ├── views/              # 8 main views
│   ├── ui/                 # shadcn/ui primitives
│   └── shared.tsx          # TrackMap, StatCard, SectionHeader
├── hooks/                  # Custom React hooks
└── lib/                    # Types, store, DB client, utils
prisma/
├── schema.prisma           # Database schema
└── seed.ts                 # Seed script

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License

MIT — see LICENSE.

Related Projects

Part of the Apex Racing F1 suite — each repo owns a distinct concern:

Repo	Role
apex-racing-live-strategy	Live race ops + discrete-event strategy simulator
f1-performance-intelligence	Telemetry ingestion, analytics dashboards, AI race engineer
predictive-tire-engine	Tire degradation ML + pit-window decision support