Gunjo · Business Intelligence for the AI Era
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AI Vertical API Packaging & Resale: Base models combined with vertical prompts to build dedicated APIs billed by usage, with top transit stations generating hundreds of thousands per month in revenue

Workflow: Daily Workflow: Scheduled early morning scripts check availability and latency of official upstream APIs such as OpenAI,

AGENT

Key Fields

FIELD STAMPS
IndustryMarketing / Advertising
RegionGlobal
ScaleSME
ChannelOnline

🔧 Workflow

Daily Workflow: Scheduled early morning scripts check availability and latency of official upstream APIs such as OpenAI, Anthropic, and Gemini (input: API keys; output: health status logs and automatic route switching). Daytime monitoring tracks own transit station call rankings and anomaly alerts, refining high-frequency general Prompt patterns into vertical preset interfaces (input: user business parameters; output: structured results processed through dedicated Prompt chains). Nightly billing generates invoices based on customers' monthly call volume and deducts fees, while updating popular vertical API documentation to the site's help page.

🛠 Setup Requirements

Required Setup: 1) Technical skills: Basic Python or Node.js API development, Docker deployment, Nginx reverse proxy, and simple billing database design (SQLite or PostgreSQL is sufficient); 2) Tools: Private server or Serverless platform, upstream multi-model API keys, payment interface (Alipay face-to-face payment or Stripe), billing middleware; 3) Time: After reusing ztoken-pro or similar open-source transit code, core setup takes about 3 to 5 days to launch, vertical Prompt tuning and documentation writing require 1 to 2 weeks of continuous iteration, followed by just 1 to 2 hours of daily maintenance.

🧰 Toolchain

  • 🔧 ztoken-pro Open-Source Transit Framework
  • 🔧 DeepSeek API
  • 🔧 Claude Anthropic API
  • 🔧 OpenAI GPT API
  • 🔧 Cloudflare Workers
  • 🔧 SQLite/PostgreSQL

💰 Revenue

① Developer and SMB team pay-as-you-go token usage (main revenue): Vertical packaging station resells at official price discounts, billed by usage (GPT text models at 15% off, Claude at 25% off, discount prices are publicly listed on the platform; e.g., $1.50 /M in · $7.50 /M out vs. official $10 / $50). Individual stations deploy 3 to 5 dedicated interfaces, making 8,000 to 30,000 RMB/month, with individual station monthly revenue almost entirely coming from this channel (approx. 100%), which is the only path listed in the card, and the figures given in the example are not independently verified with share percentages unlisted; ② Channel rebates / referral commissions: Referrers get a 30% rebate on the first order (personal ¥11.7 / team ¥59.7 / enterprise ¥299.7, also publicly listed on the platform), actual transaction numbers are unverified, and the proportion of total revenue is not provided; ③ Vertical API subscriptions: Packaging general interfaces into vertical interfaces such as legal contract review, sold at a markup per month or per call. The marked-up unit price and number of paying customers are not public, and market share is unknown; ④ Opportunities: High-value model markup space: Fable 5/5.1 on the same platform at 30% of official price, Claude at 25% off (based on platform's public listed discounts), pay-as-you-go can increase average order value, though temporary data on potential extra revenue is unavailable.

💸 Cost

Main costs are upstream API call fees (accounting for about 30% to 50% of selling price) and server fees (approx. 100 to 500 RMB per month), with no licensing fees for open-source frameworks, resulting in an overall gross margin of about 50% to 70%.

⏱ Time Investment

Initial setup requires concentrated investment of about 3 to 5 days, with daily operations taking 1 to 2 hours for monitoring and iteration.

🚀 Getting Started

Step 1: Download open-source transit projects like ztoken-pro or gpt2api from GitHub, deploy a general forwarding service using a lightweight server, and integrate low-cost models like DeepSeek. Step 2: Observe which invocation scenarios are most frequent, write 3 to 5 high-quality vertical Prompt chains for those scenarios, package them as independent POST APIs, and publish API documentation. Step 3: Share tutorials on using 'AI dedicated APIs' in technical communities such as Xiaohongshu, Jike, and Juejin, attracting developers to try them with free quotas and convert them into pay-as-you-go users.

🔑 Keys to Success

  • ✅ Vertical Prompt quality determines premium capacity: The same underlying model can be charged 5 to 10 times more per call once packaged into a legal contract review interface
  • ✅ Upstream multi-model redundant routing: Integrate at least 2 or more model API suppliers, automatically switching when a certain provider goes down or raises prices to ensure service stability
  • ✅ Niche scenario selection: Prioritize vertical fields with high call volumes and where general models are insufficiently effective (such as SEO structured generation, cross-border e-commerce multi-lingual product descriptions, code review, etc.)
  • ✅ Billing transparency and developer documentation quality: Clear call billing logs and documentation are core to the repeat purchase rate

⚠️ 风险

  • ⚠️ Upstream model providers may adjust policies to prohibit resale or lower prices to compress arbitrage space, requiring continuous searching for new low-cost models (like DeepSeek) as foundations
  • ⚠️ The pure general forwarding track has become a red ocean with fierce price wars; without transitioning to vertical packaging, gross margins will trend toward zero
  • ⚠️ If vertical prompts are reverse-engineered by competitors or targetedly optimized by general models, the premium space of packaged interfaces will be squeezed rapidly, requiring continuous iteration to maintain competitiveness

📌 Real Cases

  • 📌 Koozhan AI (koozhan.com): Full-model API transit station aggregating model interfaces from OpenAI, Claude, Gemini, and others, featuring stable forwarding and unified billing as core selling points, with monthly transaction volume reaching hundreds of thousands of RMB according to industry observations
  • 📌 Sanqian AI (GitHub project 2961799660/sanqian_ai): Open-source lightweight API transit packaging project supporting DeepSeek and other multi-model resales, with individual developers in the community already achieving 12,000 RMB/month using this framework
  • 📌 ghostai open-source transit project (GitHub AWmumu/ghostai): Fast-growing project star count; some operators packaging vertical legal contract review interfaces have achieved over 20,000 monthly calls per interface, generating about 6,000 RMB in monthly incremental revenue