Build 'TokenIQ'—a Fintech/B2B SaaS platform that acts as an 'AI CFO' to optimize LLM spending. The platform would: 1) Integrate with LLM APIs (OpenAI, Anthropic, Google) to track token usage by team, project, and user; 2) Deploy AI-driven cost optimization (e.g., 'Switch from GPT-4 to Claude Haiku for this query'); 3) Provide real-time alerts (e.g., 'Team X exceeded budget by 200%'); 4) Offer 'ROI Scorecards' to justify AI investments (e.g., 'This chatbot saved $50K in customer support'). Monetization via enterprise SaaS ($25K/year), pay-per-token savings (e.g., '10% of savings'), and CFO dashboards.

Enterprises are wasting millions on AI projects due to 'tokenmaxxing'—uncontrolled spending on LLMs without ROI tracking. Current solutions (e.g., manual usage logs, vendor-provided dashboards) lack granularity and real-time alerts. Uber’s $10M+ AI budget blowout highlights the need for guardrails. The cost of unchecked AI spending includes wasted compute ($50K+/month), lost productivity, and CFO scrutiny.