#business #idea # [[Epistemic status]] strong intuition, needs MVP testing #shower-thought #to-digest # Related - [[Ideation]] - [[Start-up ideation]] --- ## Start-up Idea: **PowerTrace** – “Plaid for Energy Footprint” --- ## Problem/opportunity No one knows the true energy or carbon cost of software — not AI companies, not enterprises, not consumers. As energy costs rise and ESG pressures increase, this blind spot becomes expensive and reputationally risky. #### Can you state the problem clearly? "Software companies and users have no visibility into the energy impact of their digital actions." #### Have you experienced it yourself? Yes — asking “how much does GPT-4 use vs Google?” is hard to answer precisely. #### Can you define the problem narrowly? Yes. Start with: energy/cost per GPT API call, per inference, per app. #### Is it solvable? Yes — use cloud + chip telemetry + estimation models + SDK. --- ## Solution A dev-facing SDK that embeds into AI or SaaS apps to estimate & expose energy/CO₂ cost per call/session/query. #### Are you affected by [[the programmer syndrome]]? A little — but it solves an enterprise compliance & branding need, not just curiosity. --- ## Markets/customers/users - AI infra providers (OpenAI API users, etc.) - SaaS platforms with ESG pressure - Internal infra/ops teams at large orgs - Climate-focused procurement teams - Consumers via browser plugin layer (later) --- ## Why - Popular: ESG/“green AI” trend is growing - Growing: regulation + carbon reporting coming - Urgent: companies will need this to avoid fines/PR disasters - Expensive: energy costs already eating margins in LLM ops - Mandatory: upcoming carbon transparency laws - [[Founder-market-fit]]: obsessed with systems transparency, AI, energy - [[What's your unfair advantage?]]: - Deep AI infra knowledge - Access to OSS + desktop telemetry layer - Could bootstrap via own LLM usage stats #energy-analytics #AI-operations