Saleen China \China

**Step 2 - Validation (Months 5-9, $500K budget)**: Expand to 3 performance metrics: (1) power delivery optimization (torque vectoring simulation), (2) thermal management (battery/motor cooling strategies), (3) racing line guidance (using GPS + IMU data). Scale to 100 beta users across 3 vehicle models (Tesla Model 3/Y/S Performance). Build cloud infrastructure for data aggregation and federated learning—each user's driving data improves the model for all users. Develop partnerships with 2-3 track day organizers (NASA, SCCA) to offer Apex AI as a 'coaching tool' for amateur racers. Success metrics: (1) 100 paying beta users at $100/month subscription, (2) measurable lap time improvements of 3-5 seconds at multiple tracks, (3) 50K+ miles of driving data collected. Validate B2B interest: pitch to 5 EV manufacturers' performance divisions (Polestar, Lucid, Rivian, Hyundai N, BMW M) for potential licensing deals.

**Step 3 - Growth (Months 10-18, $2M budget)**: Launch production hardware v1.0 ($2,000 retail) with professional installation partners (Unplugged Performance, Mountain Pass Performance). Expand vehicle compatibility to 10+ EV models through reverse-engineering and partnerships. Build viral growth loop: (1) leaderboard feature showing fastest lap times by vehicle/track (gamification), (2) referral program (give 1 month free for each referral), (3) content marketing (YouTube partnerships with EV racing channels like Out of Spec, Throttle House). Develop advanced AI features: (1) predictive maintenance (detect degradation before failure), (2) personalized driving coach (AI analyzes your mistakes and suggests improvements), (3) 'ghost car' AR feature (shows optimal racing line in real-time via phone mount). Scale to 2,000 paying users generating $100K+ MRR. Close first B2B licensing deal with a Tier-2 EV manufacturer (e.g., Polestar) to integrate Apex AI software into their performance models as a $1,500 factory option, with $500 revenue share per vehicle.

**Step 4 - Moat (Months 19-36, $10M budget)**: Build the data moat: with 10,000+ users and 10M+ miles of performance driving data across hundreds of tracks and conditions, Apex AI has the world's largest dataset of EV performance telemetry. Use this to: (1) develop vehicle-specific optimization models that outperform OEM software (e.g., 'Apex AI for Tesla' beats Tesla's Track Mode), (2) create a B2B data licensing business—sell anonymized, aggregated insights to tire manufacturers (Michelin, Pirelli), suspension companies (Öhlins), and OEMs for R&D, (3) launch 'Apex AI Pro' tier ($200/month) with advanced features like AI-generated setup recommendations for specific tracks/weather. Expand beyond performance: pivot the same AI platform to optimize efficiency (hypermiling), safety (predictive collision avoidance), and comfort (adaptive suspension tuning). This opens the TAM from 500K performance EV owners to 50M+ total EV owners. Strategic endgame: either (1) acquisition by a major OEM (Tesla, Rivian, Lucid) for $500M-$1B to integrate into their software stack, or (2) become the 'Android Auto for EV performance'—a third-party platform that every enthusiast installs regardless of vehicle brand, generating $100M+ ARR from subscriptions and B2B licensing.