Skip to content

Cloud Credits Strategy

This document outlines how we secure, allocate, and report cloud credits to support AI Wallet workloads. Objective: Define target providers, usage plan, burn-rate guardrails, milestones, and governance for credits.

Key Insights

  • Credits as runway multiplier: apply to Vercel for Startups/Accelerator and similar programs; keep optional grants in scope (e.g., Polygon) to extend experimentation runway.
  • Non-custodial funding rails: Stripe for prepaid, non-redeemable credits; optional USDC; keep stored-value risk low.
  • Governance first: strict per-user/app/org budgets, anomaly/velocity locks, immutable receipts; report burn against milestones.
  • Distribution focus: co-brand with infrastructure partners (e.g., “Powered by OpenRouter”) and publish a Vercel template; credits strategy supports partner-friendly narrative.

Sources

  • archive/AI_Wallet_Topical_Threads/MVPPlan-CloudCredits-Angels-01Nov25-ChatGPTPlus.pdf

Decisions/Implications

  • Target credits where they accelerate MVP + partner templates (Vercel Gateway compatibility); avoid locking core value to any single provider.
  • Prioritize controls (caps/kill-switch) over optimizing for the cheapest route; reliability + predictable spend beats marginal savings early.
  • Investor narrative: identity/consent/distribution is the product; credits reduce COGS and derisk pilots, not the core business.

Next Actions

  • Inventory eligible cloud/startup credit programs; draft application boilerplate and milestones.
  • Implement burn tracking tied to budgets and consent receipts; prepare a monthly credits report template.
  • Establish minimum safeguards (prepaid-only, hard caps, anomaly lock) before any scaled pilot spend.

Suggested Sections

  • Providers and program options
  • Credit ask, allocation, and tracking
  • Usage plan and cost model
  • Milestones and unlock criteria
  • Risks and contingencies
  • Reporting and compliance