Here’s a business plan for your AI company—think of it like “ChatGPT in a Guy Fawkes mask”—a private, censorship-resistant LLM service paid for with onion-routed sats. Simple. Elegant. Sovereign.
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🧠 Business Plan: “GhostQuery”
Tagline: Private Intelligence, Paid in Shadow Sats
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I. Executive Summary
GhostQuery is an AI platform delivering large language model (LLM) services with zero data retention, no user identification, and payments routed through anonymized Bitcoin microtransactions (Satoshis). It’s “Google Incognito meets ChatGPT,” but for those who understand privacy isn’t a toggle—it’s a principle.
We serve individuals and businesses who want the power of AI without sacrificing their identity, location, or data. GhostQuery doesn’t know your name, your preferences, or your history—and never will.
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II. Problem
Big AI knows too much. Every prompt you enter is logged, profiled, and turned into metadata for future monetization. Whether you’re a journalist, developer, business leader, or rebel technologist, your queries shouldn’t be feeding corporate surveillance pipelines.
People want AI utility without becoming the product.
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III. Solution
GhostQuery solves this by combining:
1. No-logging AI infrastructure: Stateless LLM API that forgets the moment it finishes your answer.
2. Onion-Routed Compute Payments: Users pay in Satoshis via the Lightning Network, tunneled through Tor or I2P.
3. Anonymous Access: No accounts, no cookies, no browser fingerprinting—access via web, desktop, or CLI using rotating onion addresses or Nostr relays.
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IV. Product Features
• Incognito LLM Queries: AI doesn’t know who you are or what you’ve asked before. That’s the point.
• Satoshi-Paid Compute: Buy compute credits in Sats. Transactions are onion-routed for absolute payer anonymity.
• Self-Hosted Option: For enterprises—air-gapped, containerized, and no-callback local LLM deployments.
• Open API: Build your own GhostQuery client with our privacy-focused SDKs (CLI, JS, Python).
• AI Quality: Mix of open-weight fine-tuned models and efficient inference hardware. You choose speed vs depth.
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V. Technology Stack
• LLM Backends: Fine-tuned open-source models (Mistral, Mixtral, Llama, etc.)
• Privacy Infrastructure:
• Tor & I2P ingress
• Lightning Network + LNURL for Sats
• No persistent storage
• No logs, ever
• Frontend:
• Lightweight Web App
• CLI and Terminal client (Go and Rust)
• Browser plugin (optional WebLN support)
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VI. Revenue Model
• Pay-Per-Prompt: You pay by the token or time with Sats. No monthly plan, no identity required.
• Enterprise Local Instances: Custom deployments for orgs that want full control over AI access and cost.
• Dev Marketplace: Let others build apps on GhostQuery API and take a fee share for compute usage.
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VII. Market
Target users:
• Privacy maximalists and cypherpunks
• Media and legal professionals (lawyers, journalists, whistleblowers)
• Developers and open-source contributors
• Bitcoiners and Lightning users
• Regulated industries with air-gapped needs
This is a growing market aligned with trends in Bitcoin, sovereign computing, and zero-trust systems.
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VIII. Go-To-Market Strategy
1. Beta via Nostr, Reddit, Hacker News, and Bitcoin Twitter
2. Sponsor privacy-focused podcasts and conferences (e.g. Advancing Bitcoin, FOSDEM)
3. Publish open-source client tools on GitHub and integrate with Umbrel/HomeLab
4. Incentivize early usage with Sats rebates via Lightning Login (optional)
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IX. Team
• Founder: You – Builder, Bitcoiner, technical PM with ethos of organic systems over centralized control
• AI/Infra Lead: TBD – ideally from the open-source LLM community
• Privacy Architect: Partner with Tor/I2P contributors
• Ops & Lightning Dev: Contract-based, active in Nostr/Bitcoin dev circles
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X. Roadmap
Phase 1: MVP
• Stateless LLM proxy server
• Lightning + Tor integration
• Basic Web UI and CLI
Phase 2: API + SDKs
• Self-hosted model delivery
• Open API + privacy SDKs
• Developer docs and client templates
Phase 3: Enterprise
• Local deployment packages
• Auditable zero-data containers
• Compliance-friendly wrappers
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XI. Funding Plan
• Initial capital: Self-funded or angel via Bitcoin-native VCs (Stillmark, Ego Death Capital, Ten31)
• Grants: Apply to OpenSats, FOSS contributors, or Human Rights Foundation
• Revenue timeline: Within 6 months, targeting profitability with 1,000 Sats-paying users/day
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XII. Exit Strategy
This company isn’t built to exit—it’s built to survive.
But hypothetically:
• Acquisition: by privacy-forward tech like Tailscale, Umbrel, or Start9
• Cooperative DAO: Transition ownership to the userbase via federated Lightning keys
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Let me know if you want a logo, pitch deck, or GitHub readme mockup to go with this. 🟧🧠🕵️♂️